Accendo Reliability
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by Mike Sondalini 3 Comments
The Importance of Fit, Tolerance & Clearance
Many equipment breakdowns and stoppages occur because of improper clearance between holes and shafts.
The shaft is too tight in the hole; the center of the hole is not at the center of the shaft making it off-center; one part is loose on another and slips out of place or does not seal as it should.
Equipment is designed so that parts have either a gap between them so they can move separately to each other or they are firmly in contact and do not move relative to each other.
The gap or lack of it between the hole and shaft is called the clearance. Clearance is determined by the size difference between the parts.
Fits and tolerances are used to specify the size range of parts.
The types of fits have been given names.
They range from an interference fit, where the parts are purposely made to be forced together. This fit can be further described as heavy through to light interference.
Whereas a clearance fit is for parts made to have a space between them.
This fit can be further described as tight through to loose.
Between these two fits is the transition fit where interference may or may not occur.
The amount of interference or clearance is achieved by specifying the tolerance range for the parts possible sizes.
Because of gradual cutting tool wear and minute changes in the machine tool internals due to temperature changes and wear/movement of internal parts, machined items can not all be made perfectly to the same dimension.
It is permitted to make the part to within a range of sizes.
That range is called the tolerance on the dimension.
Figure 1. A dimensioned and toleranced shaft and hole.
Figure 1 shows a dimensioned shaft and a dimensioned hole in a block with tolerances to provide a transition fit when assembled.
At the largest sized shaft and the smallest sized hole, they would contact.
This tolerance is too tight for a shaft that had to move through the hole but might be suitable for the outer race of a bearing fitted in a bearing housing of a rotating shaft.
In such a case the bearing race must not move on the shaft (spin) as it will wear the shaft, so an interference fit might be suitable.
If the load on the bearing was large, or there was a lot of vibration or the shaft was spinning very fast it would be better to make it a light interference fit.
If the shaft were large and rotating at low speed and repairs had to be done by the tradesman while in-the-field without access to bearing removal and installation equipment, it might be better if it was a tight clearance fit.
Selection of tolerances for a part is made after considering –
- the speed at which the part moves
- the applied loads and forces it must withstand
- the amount of vibration permitted
- whether grease or oil lubrication is used ease of assembly
- changes in size due to thermal expansion.
Engineering drawings follow a recognized standard for displaying the dimensions and tolerances required for a machined part.
Figure 2 shows two acceptable ways to dimension and tolerance a part.
Figure 2. Methods for tolerancing parts
It is critical to know the fit, tolerance, and clearance required for replacement parts.
Often damaged parts are measured up in order to manufacture a replacement.
If the old part is worn and no allowance is made for wear, the clearances will be in error and the machine may not operate properly or for long.
Fitting tolerance parts
When tolerances are too loose parts rattle about causing vibration and wear.
An oversized bore on a shaft coupling allows it to flop about on the shaft. At high speed, the coupling is thrown about causing noise, vibration and shaft distortion. Bearing failure occurs well before time.
Always machine parts to the proper size and tolerance for the application.
Drive couplings must be bored centrally and axially to prevent out-of-balance.
Bored couplings directly mounted on the shaft should have a light interference fit and be heated on assembly to slide onto the shaft and key.
Machine parts heat-up when operated and they expand and change size.
If there is insufficient clearance when the parts have expanded they may contact, or loose contact or prevent sufficient lubrication thickness to develop.
When parts make contact heat is generated and material is scraped off into the lubrication system.
Eventually, contamination and damage become severe and the machine fails.
Thermal growth of machine parts can also cause alignment changes.
There have been occasions where a machine aligned when cold, goes out of alignment when at running temperature.
Various parts have grown in length with the warmth of operation and contacted neighboring parts.
The forces generated cause deformation and distortion.
Always measure & check the research
To be certain sufficient clearance is available between parts for radial and axial thermal growth the dimensions of the parts must be measured and the clearance checked.
Corresponding dimensions of each part are measured with micrometers.
The measurements are then subtracted from each other and the difference is the clearance when the parts are cold.
In critical applications, it is necessary to determine the growth in size when the machine is at operating temperature.
The formula for thermal expansion is available from machinery handbooks. The growth in size is added to the ‘cold’ dimensions and the clearances again determined.
An example of a thermal expansion problem because of insufficient clearance for shaft axial elongation was a bearing failure on a high speed rotating 80-mm (3”) shaft.
The shaft ran on two bearings mounted in separate housings. The drive end bearing was the floating bearing and the other the fixed bearing.
This configuration, of one fixed and one floating bearing, is the correct way to allow for shaft expansion. The fixed bearing’s outer race was clamped in place inside the housing by the end covers and spacers.
However, the axial clearance between the floating bearing’s outer race and the housing’s rear cover had not been checked and was insufficient.
As the shaft grew in length with the heat of operation, the floating bearing was forced against the end cover causing tremendous heat and noise.
During assembly..
During machine assembly, the available gap between holes and shafts can be readily checked with micrometers. It is more difficult to check axial spacing.
A simple method to check axial clearance is to insert plasticine between the shoulder and the abutting face and mount the parts fully.
The plasticine is squeezed into the available space and the parts are again stripped down and the thickness of the plasticine checked with a micrometer.
Only use enough plasticine so the parts still pull-up properly together as if finally assembled.
Mike Sondalini – Maintenance Engineer
We (Accendo Reliability) published this article with the kind permission of Feed Forward Publishing, a subsidiary of BIN95.com
Web: trade-school.education E-mail: [email protected]
If you found this interesting you may like the ebook Bulk Materials Handling Introduction .
About Mike Sondalini
In engineering and maintenance since 1974, Mike’s career extends across original equipment manufacturing, beverage processing and packaging, steel fabrication, chemical processing and manufacturing, quality management, project management, enterprise asset management, plant and equipment maintenance, and maintenance training. His specialty is helping companies build highly effective operational risk management processes, develop enterprise asset management systems for ultra-high reliable assets, and instil the precision maintenance skills needed for world class equipment reliability.
November 20, 2017 at 10:21 PM
It has been a very interesting write-up and reading, thanks for your contributions to knowledge in engineering.
December 7, 2022 at 8:22 AM
Thanks for the time and energy you invested to write this information
December 7, 2022 at 11:31 AM
Thanks for the kind words. cheers, Fred
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Carrying out maintenance activities on mechanical equipment
This standard identifies the competences you need to carry out corrective maintenance activities on mechanical equipment, in accordance with approved procedures. This will involve dismantling, removing and replacing or repairing faulty components, in line with company procedures, on a variety of different types of mechanical equipment such as machine tools, gearboxes, portable tools, engines, pumps, process control valves, compressors, process plant, conveyers and elevators, lifting and handling devices, transfer equipment, mechanical structures, workholding devices and other company-specific equipment.
You will be expected to cover a range of maintenance activities, such as labelling/proof marking to aid reassembly, dismantling components to the required level, setting, aligning and adjusting components, replacing lifed' items, replenishing oils, greases or other fluids, torque loading components and making off-load' checks before testing and starting up the maintained equipment, using appropriate techniques and procedures.
Your responsibilities will require you to comply with organisational policy and procedures for the maintenance activities undertaken, and to report any problems with these activities, or with the tools and equipment used, that you cannot personally resolve or are outside your permitted authority, to the relevant people. You must ensure that all tools, equipment and materials used in the maintenance activities are removed from the work area on completion of the activities, and that all necessary job/task documentation is completed accurately and legibly. You will be expected to work to instructions, alone or in conjunction with others, taking personal responsibility for your own actions, and for the quality and accuracy of the work that you carry out.
Your underpinning knowledge will be sufficient to provide a sound basis for your work, and will enable you to adopt an informed approach to applying mechanical maintenance procedures. You will have an understanding of dismantling and reassembly methods and procedures, and their application. You will know how the equipment functions and the purpose of individual components, in adequate depth to provide a sound basis for carrying out any maintenance, repair or adjustment. In addition, you will have sufficient knowledge of these components to ensure that they are fit for purpose and meet the specifications, thus providing a sound basis for carrying out reassembly.
You will understand the safety precautions required when carrying out the maintenance activities, especially those for isolating the equipment. You will
also understand your responsibilities for safety, and the importance of taking the necessary safeguards to protect yourself and others in the workplace.
Performance criteria
You must be able to:
- work safely at all times, complying with health and safety and other relevant regulations, directives and guidelines
- follow the relevant maintenance schedules to carry out the required work
- carry out the maintenance activities within the limits of your personal authority
- carry out the maintenance activities in the specified sequence and in an agreed time scale
- report any instances where the maintenance activities cannot be fully met or where there are identified defects outside the planned schedule
- complete relevant maintenance records accurately and pass them on to the appropriate person
- dispose of waste materials in accordance with safe working practices and approved procedures
Knowledge and Understanding
You need to know and understand:
- the health and safety requirements of the area in which the maintenance activity is to take place, and the responsibility these requirements place on you
- the isolation and lock-off procedure or permit-to-work procedure that applies
- the specific health and safety precautions to be applied during the maintenance procedure, and their effects on others
- the hazards associated with carrying out mechanical maintenance activities (handling oils, greases, stored pressure/force, misuse of tools, using damaged or badly maintained tools and equipment, not following laid-down maintenance procedures), and how to minimise them
- the importance of wearing protective clothing and other appropriate safety equipment (PPE) during maintenance process
- how to obtain and interpret information from job instructions and other documentation used in the maintenance activities (such as drawings, specifications, manufacturers' manuals, symbols and terminology)
- the methods and techniques used to dismantle/assemble mechanical equipment (such as release of pressures/force, proof marking, extraction, pressing, alignment)
- methods of checking that components are fit for purpose, how to identify defects and wear characteristics, and the need to replace `lifed' items (such as seals and gaskets)
- the basic principles of how the equipment functions, its operating sequence, the working purpose of individual units/components and how they interact
- the uses of measuring equipment (such as micrometers, verniers, run-out devices and other measuring devices)
- how to make adjustments to components/assemblies to ensure that they function correctly (such as setting working clearance, setting travel, setting backlash in gears, preloading bearings)
- the importance of making `off-load' checks before running the equipment under power
- how to check that tools and equipment are free from damage or defects, are in a safe and usable condition, and are configured correctly for the intended purpose
- the importance of maintenance documentation and/or reports following the maintenance activity, and how to generate them
- the equipment operating and control procedures to be applied during the maintenance activity
- how to use lifting and handling equipment in the maintenance activity
- the activities that can go wrong when carrying out routine maintenance, and what to do if they occur
- the organisational procedure(s) to be adopted for the safe disposal of waste of all types of materials
- the extent of your own authority and to whom you should report if you have a problem that you cannot resolve
Scope/range
Scope performance.
Carry out all of the following during the maintenance activity:
- undertake the maintenance activities to cause minimal disruption to normal working
- use the correct issue of maintenance documentation (such as drawings, manuals, maintenance records)
- adhere to procedures or systems in place for risk assessment, COSHH, personal protective equipment and other relevant safety regulations
- ensure the safe isolation of equipment (such as mechanical, electricity, gas, air or fluids)
- ensure that safe access and working arrangements have been provided for the maintenance area
- report or take action with regard to any defects that require immediate attention (such as replacing non-'lifed' components)
- re-connect and return the equipment to service on completion of the maintenance activities
- dispose of waste items in a safe and environmentally acceptable manner
- leave the work area in a safe and tidy condition
Carry out maintenance activities on two of the following types of equipment:
- machine tools
- lifting and handling devices
- process plant
- portable power tools
- transfer equipment
- process control valves
- compressors
- conveyers and elevators
- mechanical structures
- workholding devices
- company-specific equipment
Maintain and/or replace six of the following types of components:
- hoses and connectors
- pulleys and belts/wires
- chains and sprockets
- levers and links
- sub-assemblies/replacement units
- structural components (such as guards, fences, supports, housings)
- locking and retaining devices (such as keys, pins, screw fasteners)
Carry out all of the following maintenance activities:
- dismantling equipment to the required level
- labelling/proof marking of components
- checking components for serviceability
- replacing all 'lifed' items (such as seals, gaskets)
- replacing or repairing damaged/defective components
- setting, aligning and adjusting components
- tightening fastenings to the required torque
- making 'off-load' checks before starting up
- replenishing oils, greases or other fluids
- functionally testing the maintained equipment
Maintain mechanical equipment, in accordance with one of the following:
- organisational guidelines and codes of practice
- equipment manufacturer's operation range
- BS, ISO and/or BSEN standards
Complete one of the following maintenance records, and pass it to the appropriate person:
- permit to work/formal risk assessment
- maintenance log and action report
- company-specific documentation
Scope Knowledge
Links to other nos, external links, version number, indicative review date, originating organisation, original urn, relevant occupations.
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Cutting & Bending
Cnc machining, finishing & assembly, knowledge base, about service, policies & terms, engineering tolerances.
In mechanical engineering, tolerances set the allowable deviation from assigned dimensions. The use of tolerances helps to ensure that the final product is readily usable, especially if it is a part of a larger assembly.
Not setting a tolerance in a critical area may render the part unusable according to the design intent, as each fabrication method comes with a certain level of inaccuracy.
However, pinpointing a suitable tolerance makes sure that the manufacturing company knows to tackle a few specific points in the production process with more attention. This can be the difference between perfectly mating parts and scrap metal.
What Is Tolerance in Engineering?
Engineering tolerance is the permissible variation in measurements deriving from the base measurement.
Tolerances can apply to many different units. For example, the working conditions may have tolerances for temperature (° C), humidity (g/m 3 ), etc. In mechanical engineering, we are mainly talking about tolerances that apply to linear, angular and other physical dimensions.
But regardless of the unit, a tolerance states an acceptable measurement range from the base point (nominal value).
Let’s say you are designing a sieve to separate 3.5 mm pebbles from 2.5 mm pebbles. You want the smaller pebbles to fall through the holes while keeping the larger ones on the sift.
The larger pieces of rocks vary in size between 3.3 mm and 3.7 mm. The smaller ones are in the range of 2.3…2.7 mm.
To ensure that only the smaller ones, all of them, will actually fall through the holes while keeping the larger ones on the sift, you can set the nominal value for the hole diameter as 2.8 mm. At the same time, manufacturing accuracy will mean that you may end up with some holes at 2.6 mm.
Adding a lower limit of -0 mm and an upper limit of +0.3 mm guarantees that all the holes will be between 2.8 and 3.1 mm in diameter.
Dimension Tolerances
As machines can not perform to perfection, the final dimensions of a product will definitely vary from the stated measurements. For example, a 15 mm hole on a drawing may end up 15.1 mm for laser cut parts .
So let’s see what you can do to make sure that the deviations are in the direction you would prefer them in. For this example, we are going to use linear dimensions.
Nominal Value
The nominal value is the basic dimension you usually give on a drawing. Without specifying the allowed tolerances, manufacturers will try to stay close to the value but there will be some sort of deviation as machine capabilities, setup, machinist competence, etc. all play a role.
Lower Deviation
Adding a lower deviation tells the manufacturer how much smaller a certain measurement can be. This is noted using the “-” sign.
When making the part on the drawing, a measurement between 99.5 and 100 mm is acceptable. Anything under or above is not within the set limits.
Upper Deviation
Upper deviation is the exact opposite of lower deviation. Adding it shows how much larger a measurement can be compared to the nominal value.
So the final measurement can be anywhere between 100 and 100.5 mm according to the tolerance limits on the drawing.
Bilateral deviation
A third way to give a tolerance range is by using bilateral deviations.
The drawing states that 99.75 is the minimum acceptable dimension and 100.25 mm is the maximum. Thus, the total “room for error” is still the same – 0.5 mm – but it can go either way from the nominal value by 0.25 mm.
A founded question here might be – is there any difference between a nominal value of 99.5 mm and an upper limit of +0.5 mm and a nominal value of 100 mm and a lower limit of -0.5 mm?
Now, if the manufacturer has made a box full of parts that fit into the range of 99.5 to 100 mm, they can send the parts out in both cases. So at this stage, there is essentially no difference.
However, the production partner will take the nominal value as the main reference point to strive for during the manufacturing phase. Thus, the 99.5 +0.5 mm box will likely contain more parts with a measurement of 99.6 mm and the 100 -0.5 mm box will come back with a larger portion of parts having a measurement of 99.9 mm.
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General Tolerances
An engineering drawing may include general tolerances in the form of a table or just a little note somewhere on the drawing (e.g. “ISO 2768-m”).
They can be applied to several conditions, including linear dimensions, angular dimensions, external radius, chamfer heights, etc. In Europe, the standard to follow is ISO 2768. ASME’s Y14.5 is the US version of a similar standard but does not cover general tolerances.
So, what does a note like ISO2768-m mean on a drawing?
That requires the manufacturer to follow the m (medium) tolerance class when making the parts. This applies to all dimensions unless stated otherwise on the drawing. Thus, a specific tolerance for a hole overrides the general tolerance requirements.
Let’s include the linear dimension table for a better explanation:
Here you can see that if a linear dimension falls into the 6 to 30 mm range, the permissible deviation is +/- 0.2 mm when looking at the m (medium) column. And for a dimension between 400 to 1000 mm, a tolerance of +/- 0.8 mm is allowed.
So 25.2 mm is acceptable for a 25 mm cut and so is 599.2 mm according to the standard for a 600 mm nominal value.
Shaft and hole matings come with a lot of different options and always require tolerances to obtain the right fit. But what is a fit in short?
Limits and fits describe the allowance between the shaft and the hole. Allowance, in turn, is the maximum dimensional difference between the diameters of the two.
There are three types of shaft-hole engineering fits.
Clearance Fit
This type of fit requires a shaft diameter to be smaller than that of the hole. Meaning that there will always be a gap between the two.
If the engineering solution needs the two to be able to slide or rotate independently of each other, this is the way to go.
So, in this case, both the shaft and the hole have tolerances that will ensure no overlapping.
Transition Fit
This option means that the maximum shaft size is bigger than the minimum size of the hole. At the same time, the minimum shaft size is also smaller than the maximum size of the hole.
So it is neither a clearance fit nor an interference one. Depending on the final measurements, the tolerances allow for both scenarios to happen while not going into extremes.
Interference Fit
Here, the shaft diameter size is always bigger than the hole. Even when the shaft is at its minimum diameter and the hole at its largest.
An interference fit ensures there is no movement between the two parts. Application of force is necessary during the physical fitting. Heating the hole, freezing the shaft and using a lubricant can all help to ease the process.
Geometric dimensioning and tolerancing adds another side to engineering tolerance basics.
The system may seem a little daunting and intricate at first but helps to convey requirements in a universally standardised way. GD&T defines the geometric tolerances for engineering products using in-part references.
For example, you can use it for defining the parallelism of two surfaces.
On the left, you can see the datum feature symbol. This assigns the left-hand surface as a reference.
The feature control frame pointing to the right side of the block has three elements – the parallelism symbol, the tolerance (distance between two parallel planes) and the datum reference.
So, what can we make of it all?
The left surface acts as a reference plane. As the machines will not be able to make both sides perfectly parallel but we require a certain limit, we gave it a parallelism tolerance.
Thus, the right side has to be parallel to the left side within a 0.1 mm tolerance, allowing for some deviation. The image above shows a possible outcome.
The right side is clearly tapered but within the limits (the green planes), therefore satisfying the set parallelism requirements.
Why Tolerance Matters & Where to Use It?
As already said, a tolerance range sets the manufacturer a boundary for deviation. If your engineering project requires a certain level of precision, there is no better way of guaranteeing it than using the tolerance system.
If you do not include them on your drawings, the manufacturer will use their in-house standard. This may be a class of general dimensions or something fully custom.
Everything measurable, from linear dimensions to weight and material hardness will always vary from part to part. When the design does not take the variation into account, components may not fit together or give too much slack, resulting in early failure.
So should you now slap on tolerances for everything, defining each pin with a maximum material condition tolerance and each hole with a minimum material condition tolerance?
No, definitely not.
First, you have to take the manufacturing method into account. It matters whether you are looking to use laser cutting or plasma cutting . The more precise the fabrication method, the more accurate tolerance you can ask for.
Secondly, precision costs. Higher demands mean that you need to pay more. So pinpoint the exact requirements only as necessary and include them in your order. Do not slap on just any tolerance here and there, or you won’t be able to compete with the market as your product prices will be wildly over the top.
If you are using our manufacturing platform to get instant quotes for STP models , just include a PDF drawing with all the necessary tolerances. We can still read all the other dimensions straight from the model, so keep the drawing simple and only mark down the info regarding dimensions that need to stay within certain limits.
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3.4: Trip Generation
- Last updated
- Save as PDF
- Page ID 47326
- David Levinson et al.
- Associate Professor (Engineering) via Wikipedia
Trip Generation is the first step in the conventional four-step transportation forecasting process (followed by Destination Choice, Mode Choice, and Route Choice), widely used for forecasting travel demands. It predicts the number of trips originating in or destined for a particular traffic analysis zone.
Every trip has two ends, and we need to know where both of them are. The first part is determining how many trips originate in a zone and the second part is how many trips are destined for a zone. Because land use can be divided into two broad category (residential and non-residential) we have models that are household based and non-household based (e.g. a function of number of jobs or retail activity).
For the residential side of things, trip generation is thought of as a function of the social and economic attributes of households (households and housing units are very similar measures, but sometimes housing units have no households, and sometimes they contain multiple households, clearly housing units are easier to measure, and those are often used instead for models, it is important to be clear which assumption you are using).
At the level of the traffic analysis zone, the language is that of land uses "producing" or attracting trips, where by assumption trips are "produced" by households and "attracted" to non-households. Production and attractions differ from origins and destinations. Trips are produced by households even when they are returning home (that is, when the household is a destination). Again it is important to be clear what assumptions you are using.
People engage in activities, these activities are the "purpose" of the trip. Major activities are home, work, shop, school, eating out, socializing, recreating, and serving passengers (picking up and dropping off). There are numerous other activities that people engage on a less than daily or even weekly basis, such as going to the doctor, banking, etc. Often less frequent categories are dropped and lumped into the catchall "Other".
Every trip has two ends, an origin and a destination. Trips are categorized by purposes , the activity undertaken at a destination location.
Observed trip making from the Twin Cities (2000-2001) Travel Behavior Inventory by Gender
Some observations:
- Men and women behave differently on average, splitting responsibilities within households, and engaging in different activities,
- Most trips are not work trips, though work trips are important because of their peaked nature (and because they tend to be longer in both distance and travel time),
- The vast majority of trips are not people going to (or from) work.
People engage in activities in sequence, and may chain their trips. In the Figure below, the trip-maker is traveling from home to work to shop to eating out and then returning home.
Specifying Models
How do we predict how many trips will be generated by a zone? The number of trips originating from or destined to a purpose in a zone are described by trip rates (a cross-classification by age or demographics is often used) or equations. First, we need to identify what we think the relevant variables are.
The total number of trips leaving or returning to homes in a zone may be described as a function of:
\[T_h = f(housing \text{ }units, household \text{ }size, age, income, accessibility, vehicle \text{ }ownership)\]
Home-End Trips are sometimes functions of:
- Housing Units
- Household Size
- Accessibility
- Vehicle Ownership
- Other Home-Based Elements
At the work-end of work trips, the number of trips generated might be a function as below:
\[T_w=f(jobs(area \text{ }of \text{ } space \text{ } by \text{ } type, occupancy \text{ } rate\]
Work-End Trips are sometimes functions of:
- Area of Workspace
- Occupancy Rate
- Other Job-Related Elements
Similarly shopping trips depend on a number of factors:
\[T_s = f(number \text{ }of \text{ }retail \text{ }workers, type \text{ }of \text{ }retail, area, location, competition)\]
Shop-End Trips are sometimes functions of:
- Number of Retail Workers
- Type of Retail Available
- Area of Retail Available
- Competition
- Other Retail-Related Elements
A forecasting activity conducted by planners or economists, such as one based on the concept of economic base analysis, provides aggregate measures of population and activity growth. Land use forecasting distributes forecast changes in activities across traffic zones.
Estimating Models
Which is more accurate: the data or the average? The problem with averages (or aggregates) is that every individual’s trip-making pattern is different.
To estimate trip generation at the home end, a cross-classification model can be used. This is basically constructing a table where the rows and columns have different attributes, and each cell in the table shows a predicted number of trips, this is generally derived directly from data.
In the example cross-classification model: The dependent variable is trips per person. The independent variables are dwelling type (single or multiple family), household size (1, 2, 3, 4, or 5+ persons per household), and person age.
The figure below shows a typical example of how trips vary by age in both single-family and multi-family residence types.
The figure below shows a moving average.
Non-home-end
The trip generation rates for both “work” and “other” trip ends can be developed using Ordinary Least Squares (OLS) regression (a statistical technique for fitting curves to minimize the sum of squared errors (the difference between predicted and actual value) relating trips to employment by type and population characteristics.
The variables used in estimating trip rates for the work-end are Employment in Offices (\(E_{off}\)), Retail (\(E_{ret}\)), and Other (\(E_{oth}\))
A typical form of the equation can be expressed as:
\[T_{D,k}=a_1E_{off,k}+a_2E_{oth,k}+a_3E_{ret,k}\]
- \(T_{D,k}\) - Person trips attracted per worker in Zone k
- \(E_{off,i}\) - office employment in the ith zone
- \(E_{oth,i}\) - other employment in the ith zone
- \(E_{ret,i}\)- retail employment in the ith zone
- \(a_1,a_2,a_3\) - model coefficients
Normalization
For each trip purpose (e.g. home to work trips), the number of trips originating at home must equal the number of trips destined for work. Two distinct models may give two results. There are several techniques for dealing with this problem. One can either assume one model is correct and adjust the other, or split the difference.
It is necessary to ensure that the total number of trip origins equals the total number of trip destinations, since each trip interchange by definition must have two trip ends.
The rates developed for the home end are assumed to be most accurate,
The basic equation for normalization:
\[T'_{D,j}=T_{D,j} \dfrac{ \displaystyle \sum{i=1}^I T_{O,i}}{\displaystyle \sum{j=1}^J T_{TD,j}}\]
Sample Problems
Planners have estimated the following models for the AM Peak Hour
\(T_{O,i}=1.5*H_i\)
\(T_{D,j}=(1.5*E_{off,j})+(1*E_{oth,j})+(0.5*E_{ret,j})\)
\(T_{O,i}\) = Person Trips Originating in Zone \(i\)
\(T_{D,j}\) = Person Trips Destined for Zone \(j\)
\(H_i\) = Number of Households in Zone \(i\)
You are also given the following data
A. What are the number of person trips originating in and destined for each city?
B. Normalize the number of person trips so that the number of person trip origins = the number of person trip destinations. Assume the model for person trip origins is more accurate.
Solution to Trip Generation Problem Part A
\[T'_{D,j}=T_{D,j} \dfrac{ \displaystyle \sum{i=1}^I T_{O,i}}{\displaystyle \sum{j=1}^J T_{TD,j}}=>T_{D,j} \dfrac{37500}{36750}=T_{D,j}*1.0204\]
Solution to Trip Generation Problem Part B
Modelers have estimated that the number of trips leaving Rivertown (\(T_O\)) is a function of the number of households (H) and the number of jobs (J), and the number of trips arriving in Marcytown (\(T_D\)) is also a function of the number of households and number of jobs.
\(T_O=1H+0.1J;R^2=0.9\)
\(T_D=0.1H+1J;R^2=0.5\)
Assuming all trips originate in Rivertown and are destined for Marcytown and:
Rivertown: 30000 H, 5000 J
Marcytown: 6000 H, 29000 J
Determine the number of trips originating in Rivertown and the number destined for Marcytown according to the model.
Which number of origins or destinations is more accurate? Why?
T_Rivertown =T_O ; T_O= 1(30000) + 0.1(5000) = 30500 trips
T_(MarcyTown)=T_D ; T_D= 0.1(6000) + 1(29000) = 29600 trips
Origins(T_{Rivertown}) because of the goodness of fit measure of the Statistical model (R^2=0.9).
Modelers have estimated that in the AM peak hour, the number of trip origins (T_O) is a function of the number of households (H) and the number of jobs (J), and the number of trip destinations (T_D) is also a function of the number of households and number of jobs.
\(T_O=1.0H+0.1J;R^2=0.9\)
Suburbia: 30000 H, 5000 J
Urbia: 6000 H, 29000 J
1) Determine the number of trips originating in and destined for Suburbia and for Urbia according to the model.
2) Does this result make sense? Normalize the result to improve its accuracy and sensibility?
- \(T_{O,i}\) - Person trips originating in Zone i
- \(T_{D,j}\) - Person Trips destined for Zone j
- \(T_{O,i'}\) - Normalized Person trips originating in Zone i
- \(T_{D,j'}\) - Normalized Person Trips destined for Zone j
- \(T_h\) - Person trips generated at home end (typically morning origins, afternoon destinations)
- \(T_w\) - Person trips generated at work end (typically afternoon origins, morning destinations)
- \(T_s\) - Person trips generated at shop end
- \(H_i\) - Number of Households in Zone i
- \(E_{off,k}\) - office employment in Zone k
- \(E_{ret,k}\) - retail employment in Zone k
- \(E_{oth,k}\) - other employment in Zone k
- \(B_n\) - model coefficients
Abbreviations
- H2W - Home to work
- W2H - Work to home
- W2O - Work to other
- O2W - Other to work
- H2O - Home to other
- O2H - Other to home
- O2O - Other to other
- HBO - Home based other (includes H2O, O2H)
- HBW - Home based work (H2W, W2H)
- NHB - Non-home based (O2W, W2O, O2O)
External Exercises
Use the ADAM software at the STREET website and try Assignment #1 to learn how changes in analysis zone characteristics generate additional trips on the network.
Additional Problems
- the start and end time (to the nearest minute)
- start and end location of each trip,
- primary mode you took (drive alone, car driver with passenger, car passenger, bus, LRT, walk, bike, motorcycle, taxi, Zipcar, other). (use the codes provided)
- purpose (to work, return home, work related business, shopping, family/personal business, school, church, medical/dental, vacation, visit friends or relatives, other social recreational, other) (use the codes provided)
- if you traveled with anyone else, and if so whether they lived in your household or not.
Bonus: Email your professor at the end of everyday with a detailed log of your travel diary. (+5 points on the first exam)
- Are number of destinations always less than origins?
- Pose 5 hypotheses about factors that affect work, non-work trips? How do these factors affect accuracy, and thus normalization?
- What is the acceptable level of error?
- Describe one variable used in trip generation and how it affects the model.
- What is the basic equation for normalization?
- Which of these models (home-end, work-end) are assumed to be more accurate? Why is it important to normalize trip generation models
- What are the different trip purposes/types trip generation?
- Why is it difficult to know who is traveling when?
- What share of trips during peak afternoon peak periods are work to home (>50%, <50%?), why?
- What does ORIO abbreviate?
- What types of employees (ORIO) are more likely to travel from work to home in the evening peak
- What does the trip rate tell us about various parts of the population?
- What does the “T-statistic” value tell us about the trip rate estimation?
- Why might afternoon work to home trips be more or less than morning home to work trips? Why might the percent of trips be different?
- Define frequency.
- Why do individuals > 65 years of age make fewer work to home trips?
- Solve the following problem. You have the following trip generation model:
\[Trips=B_1Off+B_2Ind+B_3Ret\]
And you are given the following coefficients derived from a regression model.
If there are 600 office employees, 300 industrial employees, and 200 retail employees, how many trips are going from work to home?
Measures for Managing Speed
NEWLY ADDED: WRI Low-Speed Zone Guide - Guidance on how agencies can plan, design, and implement effective low-speed zones from the World Resources Institute. This guide includes information on bringing low-speed zone designs together to fit the context as well as operating and evaluating a low-speed zones. NACTO City Limits Guide - This guidance provides practitioners a detailed, context-sensitive method to set safe speed limits on urban streets and includes a checklist guide setting context sensitive and safe speeds based on certain conditions and presence of all road users.
Traffic Calming - combination of physical measures to reduce the effects of motorist behaviors and improve conditions for all street users. Self-enforcing road - a road that encourages drivers to select operating speeds consistent with the posted speed limit.
While there are at least 4 Es for safety in the transportation profession, the first 3 Es—engineering, enforcement, and education—are critical to transportation professionals looking to reduce speeds and implement a speed management program.
Engineering for Speed Management
Transportation professionals can implement engineering strategies and countermeasures, often referred to as traffic calming, to reduce speeds on a road with higher than desired speeds. Engineering strategies and countermeasures can also be used more broadly, to change a road behavior in order to create a safer condition. A strategy is a policy or plan to heighten awareness of speed, road context, multiple road users or other safety element that may impact traveling at the safest speed. A countermeasure is an intentional alteration to the road or surrounding environment that changes the behavior of road users. The Federal Highway Administration (FHWA) Traffic Calming Eprimer module and the National Association of City Transportation Officials (NACTO) Urban Street Design Guide and Urban Bikeway Design Guide are resources related to traffic calming for transportation professionals. Additionally, NACTO also recently released a City Limits: Setting Safe Speed Limits on Urban Streets Guide that provides practitioners a detailed, context-sensitive method to set safe speed limits on urban streets. NACTO's City Limits includes a checklist to guide setting context sensitive and safe speeds based on certain conditions and presence of all road users.
When selecting an engineering strategy and/or countermeasure, transportation professionals should consider road environment, type and classification, users, crash history, cost, and effectiveness to determine the most appropriate method of traffic calming and speed reduction.
Engineering Strategies
Engineering strategies are usually comprehensive plans to re-design a road and surrounding area to change a road condition to provide a safer environment all road users. The following speed management strategies may be considered to raise awareness for safe speeds in predominantly denser land use settings:
Context Sensitive Solutions - are driven by a collaborative, interdisciplinary design process that involves all stakeholders, including citizens, to develop a road facility that fits the physical setting and the needs of the public. Context sensitive design involves accommodating all street users, making decisions that reflect a shared stakeholder vision, and demonstrating an understanding of the tradeoffs that come with balancing multiple needs on, typically, complex urban roads. The ITE Implementing Context Sensitive Design on Multimodal Corridors: A Practicioner's Handbook , Designing Walkable Urban Thoroughfares: A Context Sensitive Approach and FHWA Context Sensitive Solutions and Design are helpful resources for transportation professionals considering a context sensitive solutions related to speeding and safety. The World Resources Institute (WRI) Low-Speed Zone Guide presents strategies for planning, designing, building, and evaluating low-speed zones in cities in the U.S. and internationally.
Complete and Shared Streets – Complete are roads designed for use by all modes of transportation and shared streets are roads where all users are given equal priority by minimizing the segregation between modes of transportation. Roads have predominately been designed giving priority to motor vehicles, but now roads, especially urban streets, are being re-designed to incorporate safe paths of travel for all road users, from pedestrians to bicyclists. The type of street, the context and diversity of users determine whether a complete street or a shared street are the safest strategy for a road. Providing facilities for all road users reduces congestion by motorists and creates a safer environment for all road users. The Smart Growth America National Complete Streets Coalition provides resources for transportation professionals on completes streets, including the Safe Streets Academy and the Dangerous by Design reports. Additionally, the American Planning Association report Complete Streets: Best Policy and Implementation Practices and the FHWA guide Achieving Multimodal Networks Applying Design Flexibility & Reducing Conflicts are helpful resources when implementing complete streets.
Self-enforcing Roadways - The application of self-enforcing roadways is one possible approach to manage speeds. It encourages driver speed choice that is compliant with the regulatory speed limit. The FHWA report Self-Enforcing Roadways: A Guidance Report published in January 2018, describes six self-enforcing road concepts that may be used to design roadways that produce operating speeds consistent with the desired operating speeds of the roadway.
Engineering Countermeasures
Engineering countermeasures are used on an existing road to change undesirable behaviors, such as reducing speeds and/or congestion on a road or road network. Traffic calming is a physical alternation implemented either based on engineering strategies or when speed is identified as a problem. Speed management countermeasures consist of horizontal, vertical, lane narrowing, roadside, and other features that use physical or psycho-perception means to produce desired effects. Traffic calming measures can be categorized into the following categories:
Horizontal deflection hinders the ability of a motorist to drive in a straight line by creating a horizontal shift in the roadway. This shift forces a motorist to slow the vehicle in order to comfortably navigate the measure. Examples of types of horizontal deflections are features are lateral shifts, chicanes, roundabouts, etc.
Vertical deflection creates a change in the height of the roadway that forces a motorist to slow down in order to maintain an acceptable level of comfort. Examples of types of vertical deflection are features such as speed humps, cushions, tables, raised crosswalks, etc.
Street width reduction narrows the width of a vehicle travel lane. As a result, a motorist slows the vehicle in order to maintain an acceptable level of comfort and safety. The measure can also reduce the distance a pedestrian walks to cross a street, reducing exposure to pedestrian/vehicle conflicts. Examples of types of street width reduction are features such as road diets, corner extensions, medians or pedestrian refuge islands, on-street parking, etc.
Other countermeasures may not fit into any of the above categories but are often awareness mechanisms to reduce speeds, including, but not limited to speed feedback signs, high visibility pavement markings, enhanced curve delineation, stoplight reflective borders, etc.
Most often, multiple engineering countermeasures are installed to create a truly safe road for all users, often referred to as a self-enforcing road. The FHWA Engineering Speed Management Countermeasures: A Desktop Reference of Potential Effectiveness in Reducing Speed outlines engineering countermeasures appropriate for implementation based on road type, volume, speed, and safety concern. The ITE Traffic Calming website outlines all types of engineering countermeasures available to reduce speeds. The FWHA document Making Our Roads Safer One Countermeasure at a Time, 20 Proven Safety Countermeasures that offer significant and measurable impacts to improving safety is very helpful in providing basic design guidance and statistical information on the safety benefit of each engineering countermeasure. The FHWA Road Diet Informational Guide and Pedestrian and Bicycle Safety Guide and Countermeasure Selection System , the National Highway Traffic Safety Administration (NHTSA) Countermeasures That Work: A Highway Safety Countermeasure Guide For State Highway Safety Offices and the iRAP Road Safety Toolkit also provide guidance on traffic calming.
Enforcement for Speed Management
Enforcement is critical to achieving a safe use of roads, compliance with speed limits, and ensuring overall movement at a safe speed. According to NHTSA, more than half of all traffic stops result from speeding violations. Transportation professionals assist enforcement authorities to ensure speed enforcement is fair, rational, and motivated by safety concerns.
Traditional Enforcement
Traditional enforcement involves patrol officers monitoring where crashes related to speeding have occurred and/or where violations of the speed limit occur. To be effective over the long term, traditional enforcement measures need to be consistent, sustained, and must provide data back to transportation professionals to assist in evaluation of road designs. Transportation professionals should remain involved in traditional enforcement to monitor proper posting of signs and other elements of maintaining a speed management program.
Automated Speed Enforcement (ASE)
Enforcement of speed limits can also be accomplished through the use of automated speed cameras that record a vehicle speed using radar and a camera that captures the vehicle when the threshold speed is exceeded. Violation evidence is processed and reviewed in an office environment and violation notices are delivered to the registered owners of identified vehicles after the alleged violation occurs. Transportation professionals should be involved in determining the location and type of automated speed enforcement with law enforcement professionals. Fixed ASE units are permanently mounted in fixed locations, in areas such as school zones; semi-fixed and mobile ASE units are mounted to housing, a vehicle or trailer to allow for mobile enforcement as needed, such as in construction zones; and speed-on-green ASE units are typically used to detect red light violations but can also detect speed violations through intersections.
Automated speed enforcement allows for a high rate of violation detection, increases safety of first responders, and ensures consistent enforcement of speeds. However, automated speed enforcement delays violation and penalty, is limited in the range of enforcement, and may limit the ability to educate offenders. Automatic speed enforcement should be used to solve a safety problem where engineering measures cannot be installed to calm traffic. Often, state laws determine the use of automatic speed enforcement and limits local implementation.
The NHTSA Speed Enforcement Camera System Operational Guidelines provides guideance on ASE operations. The Insurance Institute for Highway Safety (IIHS) Highway Loss Data Institute tracks state laws on automated speed enforcement and also provides other resources related to ASE. The National Transportation Safety Board (NTSB) Reducing Speeding-Related Crashes Involving Passenger Vehicles , the NHTSA System Analysis of Automated Speed Enforcement Implementation and the Pedestrian and Bicycle Information Center An Overview of Automated Enforcement Systems and Their Potential for Improving Pedestrian and Bicyclist Safety are also helpful resources on automatic speed enforcement.
IIHS has also conducted research into Intelligent Speed Assistance (ISA) and provides information on how ISA technology is being explored to encourage safer vehicle speeds. The European Union recently passed legislation requiring Intelligent Speed Assistance in all new car by 2022.
Education for Speed Management
The NHTSA Highway Safety Program Guideline on Speed Management suggests the following actions for education and communication:
- Develop and evaluate culturally relevant public awareness campaigns to educate drivers on the importance of obeying speed limits and the potential consequences of speeding;
- Use market research to identify and clearly understand how, when, and where to reach high-risk drivers;
- Develop a strategy to educate the public about why and how speed limits are set;
- Capitalize on special enforcement activities or events such as saturation patrols and sobriety checkpoints, impaired driving crackdowns, occupant protection mobilizations, and other highly publicized sustained enforcement activities;
- Identify and collaboratively support efforts of highway safety partners, traffic safety stakeholders, and health and medical communities to include speed management as a priority safety, economic, and public health issue; and
- Promote responsible driver behavior and speed compliance in advertising.
FHWA Traffic Safety Marketing program offers speeding prevention campaign information. The World Health Organization (WHO) Road Safety communication materials on speeding and speed management.
Travel settings
Nov 8, 2022 • knowledge, information, article details, enable retraction.
Retraction is used at the places in a print where the printer has to do a travel move between two printed parts. Without retraction, extruded material will hang between the parts. By using retraction, “stringing” (thin threads of plastic in between the printed parts) is prevented, resulting in a much cleaner model. Exercise caution when using flexible materials or models that require a lot of retractions as it may lead to grinding of the filament.
Retract at layer change
This setting forces the printer to retract the filament before it starts printing the next layer.
Retraction distance
This is the distance in millimeters that the material is retracted from the nozzle. A long retraction creates more stress on the material, takes time and minimizes oozing. A short retraction has an increased chance of oozing, but keeps the material secure and print time shorter.
Retraction speed: retract and prime
This refers to the speed, in millimeters per second, at which the material is retracted and primed. A high-speed retraction minimizes oozing, but can cause material grinding. A low-speed retraction has an increased chance of oozing, but will protect the material.
Retraction extra prime amount
This is the extra amount of material that is extruded after a retraction to compensate for oozed material after a travel move. This setting can be useful, especially with flexible filaments as these require extra pressure to print properly. By increasing the retraction extra prime amount, more pressure is added which helps compensate for the material.
Retraction minimum travel
This setting determines the minimum distance the print head must travel before a retraction move is initiated. With retraction-intensive models, you could increase the value, which decreases the number of retractions and reduces the possibility of grinding. However, the value must not be set too high as this might lead to stringing and cause ugly “blobs” to form on the print.
Maximum retraction count
The maximum retraction count sets the maximum number of retractions on a certain length of filament (see minimum extrusion distance window). All retractions above this value will be ignored. The benefit of maximizing the amount of retractions is that it decreases the possibility of grinding. However, for models with a lot of holes (e.g. a voronoi print), this can lead to stringing if the value is too low.
Minimum extrusion distance window
This is the length of filament over which the maximum retraction count is enforced. This value protects the number of retractions on the same piece of filament.
For example: If you set the maximum retraction count to 25 and the minimum extrusion distance window to 1.0 mm, it will do a maximum of 25 retractions per 1.0 mm extruded filament.
Combing Mode
Combing will reduce the chance of defects on outer surfaces of the print by recalculating all nozzle travel moves to stay within the perimeter of the print. This results in greater travel distances, but with a reduced need for material retraction.
If combing is disabled, the material will retract and the print head will move in a straight line to the next point.
Avoid printed parts
By enabling this setting, the print head will avoid printed parts when traveling. When the shortest route from one point to another in the print is obstructed, the print head will move around it. This decreases the possibility of coming into contact with parts of the model that have already been printed, in turn reducing the chance of surface defects or material mixing. To use this setting, you must first enable combing.
Avoid distance
This setting defines the distance (in mm) between the nozzle and the print when avoid already printed parts is enabled. A greater avoid distance means a reduced chance of contact with the printed model, however a large avoid distance will significantly affect the length of the travel moves, impacting the print time, and chance of oozing.
Layer start X-Y
This setting defines the position closest to these coordinates to start the next layer. The setting is normally set to the far-right corner because that is where the Ultimaker 3's switching bay is located.
Note: This is a different setting than the Z-seam. The z-seam alignment setting only adjusts the start position of the outer wall, where this setting normally starts at the infill.
Z-hop when retracted
With this setting, the build plate will move down by the set value when a retraction is performed, allowing the print head to travel over the print without the nozzle touching it. This prevents the nozzle from hitting the object or leaving “blobs” or scratches on the print surface. Please note that for prints with lots of retractions/travel moves, this can increase the print time.
Z-hop only over printed parts
The 'Travel' category includes the option 'Avoid printed parts'. When this is enabled, the nozzle will avoid these parts when possible in order to reduce scratching the model’s surface. When there is no way to avoid the part, the printer will perform a Z-hop when traveling over the part.
Z-hop height
This setting specifies the height (in mm) at which all Z-hop moves are performed during the print.
Z-hop after extruder switch
This feature will trigger a Z-hop when the nozzle moves to the switch bay, reducing the chance that oozed material will come in to contact with the printed model.
Continue reading about Cooling settings.
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Part III: Travel Demand Modeling
9 Chapter 9: Introduction to Transportation Modeling: Travel Demand Modeling and Data Collection
Chapter 9 is the prelude to travel demand modeling, an essential task in transportation planning and policy analysis. As discussed in previous chapters, the spatial distribution of activities like jobs, residents, and transportation systems have mutual impacts on each other. The travel demand forecasting techniques will create dynamic processes in urban areas. A clear understanding of travel demand modeling is essential for anyone interested in transportation planning and practice. This chapter elicits the basics of the four-step traditional travel demand modeling. It discusses the necessary procedures for the model applications, like determining the goals and criteria, defining scenarios, developing alternatives, collecting data, and conducting forecasting and evaluation.
Learning Objectives
Student Learning Outcomes
- Describe the need for travel demand modeling in urban transportation and relate it to the structure of the four-step model (FSM).
- Summarize each step of FSM and the prerequisites for each in terms of data requirement and model calibration.
- Summarize the available methods for each of the first three steps of FSM and compare their reliability.
- Identify assumptions and limitations of each of the four steps and ways to improve the model.
Prep/quiz/assessments
- What is the need for regular travel demand forecasting, and what are its two major components?
- Describe what data we require for each of the four steps.
- What are the advantages and disadvantages of regression and cross-classification methods for a trip generation?
- What is the most common modeling framework for mode choice, and what result will it provide us?
- What are the main limitations of FSM, and how can they be addressed? Describe the need for travel demand modeling in urban transportation and relate it to the structure of the four-step model (FSM).
9.1 Introduction
Travel demand modeling is among the most critical tasks of transportation planning and policy analysis because it provides factual support when we suggest or analyze a policy or program through different scenarios. In this course, we have primarily discussed the relationship between urban activities or land uses and travel demands and the role of transportation systems in between. Figure 9.1 represents the same idea with a slightly different angle, which is more from the transportation planning side. This model shows how all these variables impact each other in a sequential format and create the loop. For instance, the number of jobs and households, which are the model’s inputs in the middle of the loop, change the model’s results and finally change the plan, which is the model’s output. The plan outcomes again leave impacts on the inputs in future sequences.
This is because, transportation has a direct impact on mobility, economic robustness, and environmental quality. Thus, planning is needed to provide agile, high-quality, and sustainable services with minimum costs. Transportation planning deals with different kinds of problems and tasks. Transportation plans are crucial for shaping the future characteristics of transportation services and usually have long-range goals. Making a balance between supply (new highway development or public transit improvement) and demand (demand for travel with different purposes) is one crucial task. Below, some other specific tasks that transportation planners address are listed, according to the Federal Highway Administration and Federal Transit Administration (2007):
- Travel demand modeling for congestion reduction
- Integrating land use and transportation studies
- Fuel consumption reduction measures
- Environmental assessment
- Safety measures
- Developing congestion pricing schemes
- Freight movement planning
- Analyze accessibility to different activities
- Public transit planning
- Public engagement
- Improvement of intermodality and multimodality.
In transportation planning, travel demand models forecast how people travel. This forecasting includes how thousands of individuals decide when, where, and how they should travel. Many factors (including living arrangements, characteristics of the person making the trip, and available destination choices, route choices, and mode choices for completing the trip) influence these decisions. Mathematical relationships use existing data to represent human behavior in these decisions. Through a sequential process in transportation planning, the following questions can be answered based on modeling estimation:
- What does the future of the area look like?
- What is the population in the forecasting year?
- What is the distribution and categorization of job opportunities?
- What are the travel patterns in the future?
- How many trips will people be making? (Trip Generation)
- Where will the trips end? (Trip Distribution)
- What transportation mode will be used? (Mode Split)
- What will the demand be for different corridors, highways, and streets? (Traffic Assignment)
- And finally, what kind of impact will this modeled travel demand have on our area? (Rahman, 2008).
9.2 Four-step Model
According to this objective, we can perform transportation modeling in two stages. In the first stage, we observe and collect data on travelers’ characteristics and land use and calibrate our model to generate a total trip table between TAZs. Next, these trips are assigned to different destinations and modes and finally to the network to calculate the total demand for each road segment. Through this second stage, a few other choices, such as the time of day for travel and whether to travel or not, can be modeled using choice models (McNally, 2007). This process, called four-step travel demand modeling (FSM), is considered very accurate for aggregate calculations but sometimes fails to perform a reliable policy test. Figure 9.2 shows a simple structure of FSM.
9.2.1 Stage 1
In the first stage, we develop an understanding of the study area from demographic information and urban form (land-use distribution pattern). These are important for all the reasons we discussed in this book. For instance, we must obtain the current age structure of the study area, based on which we can forecast future birth rates, death, and migrations (Beimborn & Kennedy, 1996).
Regarding economic forecasts, we must identify existing and future employment centers since they are the basis of work travel, shopping travel, or other travel purposes. Empirically speaking, employment often grows as the population grows, and the migration rate also depends on a region’s economic growth. A region should be able to generate new employment while sustaining the existing ones based upon past trends and form the basis for judgment for future trends (Mladenovic & Trifunovic, 2014).
After forecasting future population and employment, we must predict where people go (work, shop, school, or other locations). Land-use maps and plans are used in this stage to identify the activity concentrations in the study area. Future urban growth and land use can follow the same trend or change due to several factors, such as the availability of open land for development and local plans and zoning ordinances (Beimborn & Kennedy, 1996). Figure 9.3 shows different possible land-use patterns frequently seen in American cities.
Land-use pattern can also be forecasted through the integration of land use and transportation as we explored in previous chapters.
9.2.2 Stage 2
Travel forecasting is necessary in urban transportation studies. We can simulate human behavior using mathematical series and calculations. The sequence of different steps is associated with different choices commuters make within an urban setting. The first attempt at this kind of analysis in the U.S. was during the era of post-war development with fast economic growth. The landmark study of Mitchell and Rapkin (1954) called for establishing a link between travel and activities and highlighted the need to develop a comprehensive framework.
The initial development models of trip generation, distribution, and diversion in the 1950s led to the application of FSM for a Chicago area transportation study. This model was highway-oriented, and the goal was to compare new facility development and improved traffic engineering. In the 1960s, federal legislation mandated comprehensive and continuous transportation planning and institutionalized FSM. During the 1970s, scholars found that the model needed to be revised to address emerging concerns such as environmental issues or multimodal systems. Thus, improvements led to the creation of dissagregated travel demand models and equilibrium assignment methods that integrated well with FSM. Today, FSM has successfully helped forecast travel demand for more than 50 years (McNally, 2007; Weiner, 1997).
Mannheim (1979) outlined the basic structure of FSM, and Florian, Gaudry, and Lardinois (1988) later expanded the model. Figure 9.4 shows different influential components of travel demand (modeling). T, which refers to transportation, comprises all elements related to the transportation system and its services. A is the activity system defined according to land-use patterns and socio-demographic conditions. P refers to transportation network performance, and D, which is demand, is generated based on the land-use pattern. According to Florian, Gaudry, and Lardinois (1988), L and S (location and supply procedures) are optional parts of FSM and rarely are integrated into the model.
A critical point is understanding units in the procedures defined spatially and temporally. Demand produces person trips, which reflect time and space (e.g., person trips per household or rush-hour person trips by zone). Performance typically produces a level of service defined as a link volume capacity ratio (e.g., vehicle trips per hour, or ridership (boarding) per hour for a public transit). We define demand at the zonal level and performance at the link level.
It is also important to note that applying travel forecasting models such as FSM is continuous. Generating results from these models is long and daunting enough that many changes may occur in our study area during our analysis. Before we go through the four steps of FSM, we need to find ways to define our study area. Identical to most of the models we have reviewed thus far, FSM uses traffic analysis zones, known as TAZs, for the geographic unit of analysis. However, a more significant number of TAZs generate more accurate results for us. The number of TAZs in the model can vary based on our purpose, data availability, and model vintage. These zones are characterized or categorized by population, employment, and other factors. For modeling simplicity, one general assumption of the FSM model is that trip-making begins at the center of a zone ( zone centroid ). Also, trips that are very short and begin and end inside a TAZ, like the ones by bike or on foot, are usually not included in the model.
Moreover, we consider highway systems and transit systems as networks for the model. The network consists of links such as segments of a highway or transit line and nodes as intersections. Travel times, speeds, capacity, and directions can represent data about the network conditions. With this kind of information, we perform the travel simulation process. Trips begin in the trip generation zone or origin, move through the network which consists of links and nodes, or transit lines and end at a trip attraction zone.
9.2.3 Trip Generation
As already mentioned, FSM’s first step is trip generation. This step helps us define the magnitude of daily travel in our study area for different trip purposes. This step will provide us with an estimate of the total trips to and from each zone, creating a trip production and attraction matrix for each trip purpose. Trip purposes in FSM are home-based work trips (work trips that begin or end at home), home-based shopping trips, home-based other trips, school trips, non-home-based trips (trips that neither begin nor end at home), truck trips, and taxi trips (Ahmed, 2012). Trip attractions are based on the level of employment in a zone. In the trip generation step, we have some assumptions and limitations as below:
- Independent decisions: Travel behavior is affected by many factors generated within a household; the model ignores most of these factors. For example, childcare may force people to change their travel plans.
- Limited trip purposes: This model consists of a limited number of trip purposes for simplicity, giving rise to some model limitations. Take shopping trips, for example; they are all considered in the same weather conditions. Similarly, we generate home-based trips for various purposes (banking, visiting friends, medical reasons, or other purposes), all of which are affected by factors ignored by the model.
- Trip combinations: As we all do daily, travelers are often willing to combine various trips into a chain of short trips. While this behavior creates a complex process, the FSM model treats this complexity in a limited way.
- Feedback, cause, and effect problems: trip generation often uses factors that are a function of the number of trips. For instance, for shopping trip attractions in the FSM model, we assume they are a retail employment function. However, it is logical to assume how many customers these retail centers attract. Alternatively, we can assume that the number of trips a household makes is affected by the number of private cars they own. Nevertheless, the activity levels of families determine the total number of cars.
As mentioned, trip generation process estimations are done separately for each trip purpose. Equations 1 and 2 show the function of trip generation and attraction:
Oi=f(xi1, xi2, xi3, …)
Di=f(yj1, yj2, yj3, …)
where Oi and Dj trip are generated and attracted respectively, x refers to socio-economic characteristics, and y refers to land-use properties.
Generally, three different trip purposes exist in any FSM model: home-based work trips (HBW) , home-based other (or non-work) trips (HBO) , and non-home-based trips (NHB) . Trip ends are either the origin (generation) or destination (attraction), and home-end trips comprise most trips in a study area. We can also model trips at different levels, such as zones, households, or person levels (activity-based models). Household-level models are the most common scale for trip productions, and zonal-level models are appropriate for trip attractions (McNally, 2007).
There are three main methods for a trip generation or attraction. The first method is multiple regression based on population, jobs, and income variables. The second method in this step is experience-based analysis, which can show us the ratio of trips generated frequently. The third method is cross-classification . Cross-classification is similar to the experience-based analysis in that it uses trip rates but in an extended format for different categories of trips (home-based trips or non-home-based trips) and different attributes of households, such as car ownership or income. To elaborate on the differences between these methods, category models are more common for the trip generation model, while regression models have better performance for trip attractions (Meyer, 2016). Production models are acknowledged to be influenced by a variety of explanatory and policy-sensitive variables (e.g., car ownership, household income, household size, and the number of workers). However, the estimation is more problematic for attraction models because regional travel surveys are at the household level (thus providing more accurate production models) and not for nonresidential land uses (which is important for trip attraction). The estimation can also be problematic because explanatory trip attraction variables may usually underperform (McNally, 2007). Thus, it is important to collect survey data prior to relating sample trips to population-level attraction variables. A regression analysis is is usually used for this calibration. Table 9.1 shows the advantages and disadvantages of each of the two models.
Table 9.1 Advantages and disadvantages of regression and cross-classification methods
Adapted from: McNally, 2007
9.2.4 Trip Distribution
Thus far, we have calculated the number of trips beginning or ending in a particular zone. In the second step, we are willing to see how trips get distributed between zones and how many trips get exchanged between two particular zones. Imagine a shopping trip; you have multiple options among several shopping malls accessible to you. However, in the end, you will choose one of them for your destination. We model this information in trip distribution as the second step. The second step results are usually a very large O-D matrix for each trip purpose. The O-D matrix can look like the table below (9.2), in which sum of Tij by j shows us the total number of trips attracted in zone J and the sum of Tij by I yield the total number of trips produced in zone I.
Table 9.2 Sample trip distribution results
The gravity model developed by Hansen (1959), , elaborated in previous chapters, will be used to calculate the trip distribution. This model, a spatial interaction model, considers the trip produced and attracted for each zone as a contributing factor and the distance between them as an impedance function (Rodrigue, 2020). Recall from previous chapters that the gravity model formula is as follows:
T ij = trips produced at I and attracted at j
P i = total trip production at I
A j = total trip attraction at j
F ij = a calibration term for interchange ij , (friction factor) or travel
time factor ( F ij =C/t ij n )
C= calibration factor for the friction factor
K ij = a socioeconomic adjustment factor for interchange ij
i = origin zone
n = number of zones
We can use different methods (units) in the gravity model to perform distance measurements. For instance, distance can be represented by time, network distance, or travel costs. For travel costs, auto travel cost is the most common and straightforward way of monetizing distance. A combination of different costs, such as travel time, toll payment, parking payment, etc., can also be used. Alternatively, a composite cost of both car and transit costs can be used (McNally, 2007).
Generalized travel costs can be a function of time divided into different segments. For instance, public transit time can be divided into in-vehicle time, walking time, waiting time, interchange time, fare, etc. Since travelers perceive time value differently for each segment (like in-vehicle time vs. waiting time), weights are assigned based on the perceived value of time (VOT). Similarly, car travel costs can be categorized into in-vehicle travel time or distance, parking charge, tolls, etc.
As with the first step in the FSM model, the second step has assumptions and limitations.
- Constant trip times: To use the model for prediction, we must assume that the length of trips remains constant. Because we measure the length by travel time, we assume that improvements in the transportation system that reduces travel times are balanced by separating origin and destinations.
- Use automobile travel times to represent distance: We use travel time as a proxy of travel length. In the gravity model, this is mainly based on private car travel time and disregards travel times by other modes such as public transit. The result will be a wider distribution of trips.
- Limited effect of social-economic-cultural factors: As you have probably guessed, disregarding some socioeconomic or cultural factors is another limitation in the gravity model. In fact, in this model, the basis for the prediction is trip production and attraction and travel times between them. As a result, we eventually estimate high trip rates between high-income groups and nearby low-income TAZs. Thus, the more accurate results will be when we incorporate more socioeconomic factors into the model.
- Feedback Problems: Congestion levels on the roads highly affects the travel time we are willing to plug into the gravity model. Nevertheless, the congestion level is an unknown measurement since we will find out about it in the following steps. Typically travel times are assumed and checked later. If the assumed values does not match the actual values, they should be modified, and we should redo the calculations.
9.2.5 Mode choice
FSM model’s third step is a mode-choice estimation that helps identify what transportation means users will utilize for different trip purposes to offer information about users’ travel behavior. This usually results in generating the share of each transportation mode (in percentages) from the total number of trips in a study area using the utility function (Ahmed, 2012). Performing mode-choice estimations is critical because it determines the relative attractiveness and usage of different modes, such as public transit, carpooling, or private cars. Modal split (choice models) can help assess any improvement program or proposal (such as congestion pricing or parking charges) that seeks to improve accessibility or transportation’s level of service. It is essential to determine what factors comprise the utility and disutility of different modes for various travel demands (Beimborn & Kennedy, 1996). Comparison of the disutility of different modes between two points can help us determine the mode share. Disutility, in general, refers to burdens of making a trip such as time, cost (fuel cost, parking cost, toll, etc.), and convenience. Once we model disutility for different trip purposes between two points, we can assign all trips to different modes based on their utility. As you will see in Chapter 12, an advantage of one mode compared to another in terms of utility can result in a high share of trips using that mode. The assumptions and limitations for this step are outlined below:
- Choices are only affected by travel time and cost: In this model, we assume that changes in mode choices will only occur if we change transportation cost or travel time in the transportation network or transit system. For example, a more convenient mode of transit with the same travel time and cost makes no difference in the model’s results.
- Omitted factors: Some factors not included in the model, like crime, safety, security, etc., are assumed to have no effect, although we assume they are included due to the calibration process. However, modes with different attributes in terms of omitted factors make no difference in the results.
- Access times are simplified: Quality of access, such as ease of walking in a neighborhood regarding safety, walkability, weather conditions, etc., are usually neglected. As a result, walkability or the effect of a bike-sharing program on the utility of different modes does not enter the model.
- Constant weights: The importance of time and cost of travel in the mode choice is assumed to be constant for any given trip purpose. However, there is a wide variety of trip purposes, and travelers give importance to travel time and cost differently for different trip purposes.
A nested logit model is the most common framework of mode choice models, which can incorporate a wide range of explanatory variables. However, we must aggregate results for each zone before the last step (Koppelman & Bhat, 2006).
A general chart of modal split is shown in Figure 9.5:
In our analysis, we can use binary logit models (dummy variable for dependent variable) if we have two modes of transportation (like private cars and public transit only). A binary logit model in the FSM model shows us if particular changes in travel costs would occur, such as what portion of trips changes by a specific mode of transport. The mathematical form of this model is:
where: P_ij 1= The proportion of trips between i and j by mode 1 . Tij 1= Trips between i and j by mode 1.
Cij 1= Generalized cost of travel between i and j by mode 1 .
Cij^2= Generalized cost of travel between i and j by mode 2 .
b= Dispersion Parameter measuring sensitivity to cost.
It is also possible to have a hierarchy of transportation modes for using a binary logit model. For instance, we can first conduct the analysis for the private car and public transit and then use the result of public transit to conduct a binary analysis between rail and bus.
9.2.6 Trip assignment
Once we get the trip counts disaggregated by the modal split, we find the specific path the commuters use to reach their destinations from their origin, particularly for private car trips. This estimation is called trip assignment and is the most complex step among all the steps in the FSM model. The minimum path assigns trips for each O-D pair based on travel costs or time. Then, the assigned trip volume is compared to the capacity of that link to see if it would be congested. If congestion occurs (meaning that the traffic volume is greater than the capacity), the speed of the link should be reduced, which results in more significant travel costs or time. Once the Volume/Capacity (v/c ratio) changes, the speed and shortest path may change due to congestion. This feature of the model necessitates the use of an iterative process until an equilibrium is reached.
Similarly, the process for public transit is the same, with one difference. In public transit, headways should be adjusted instead of travel times since headways’ duration affects each transit vehicle’s capacity and volume (ALMEC, 2015). The concept of equilibrium in the trip assignment step is very crucial to understand because this concept can tell us if a model should stop the iteration process or continue. This equilibrium concept is named Wardrop equilibrium . In Wardrop equilibrium conditions, traffic arranges itself in congested networks so that no individual trip maker is willing to change his route to reduce travel time/costs (Hadi, Ozen, & Shabanian, 2012). Also, another critical factor in this step is the time of the day.
Like previous steps, the following assumptions and limitations are pertinent to the trip assignment step:
- Delays on links: Most traffic assignment models assume that delays occur on the links, not the intersections. For highways with extensive intersections, this can be problematic because intersections involve highly complex movements. Intersections are excessively simplified if the assignment process does not modify control systems to reach an equilibrium.
- Points and links are only for trips: This model assumes that all trips begin and finish at a single point in a zone (centroids), and commuters only use the links considered in the model network. However, these points and links can vary in the real world, and other arterials or streets might be used for commutes.
- Roadway capacities: A simple assumption helps determine roadways’ capacity in this model. Capacity is found based on the number of lanes a roadway provides and the type of road (highway or arterial).
- Time of the day variations: As we all have seen and experienced, traffic volume varies significantly throughout the different times of the day and the week. In this model, a typical workday of the week is considered and converted to peak hour conditions. A factor used for this step is called the hour adjustment factor. This value is critical because a small number can result in a massive difference in the congestion level forecasted on the model.
- Emphasis on peak hour travel: The model forecasts for the peak hour but does not forecast for the rest of the day. The models make forecasts for a typical weekday but neglect specific conditions of that time of the year. After completing the fourth step, we get precise approximations of travel demand or traffic count on each road. Further models can be used to simulate transportation’s negative or positive externalities. These externalities include air pollution, updated travel times, delays, congestion, car accidents, toll revenues, etc. These need independent models such as emission rate models (Beimborn & Kennedy, 1996).
The basic equilibrium condition point calculation is an algorithm that involves the computation of minimum paths using an all-or-nothing (AON) assignment model to these paths. However, to reach equilibrium, multiple iterations are needed. In AON, we assume that the network is empty and a free flow is possible, and thus we perform the first iteration of the AON assignment, which means loading the traffic by finding the shortest path. Due to congestion and delayed travel times, the previous shortest paths may no longer be the best minimum path for a pair of O-D. If we observe a notable decrease in travel time or cost in subsequent iterations, then it means the equilibrium point is unreached, and we must continue the estimation. Typically, the following factors affect private car travel times: distance, free flow speed on links, link capacity, link speed capacity, and s peed flow relationship .
The relationship between the traffic flow and travel time equation that we use in the fourth step is:
t=t 0 +av n v<c
t=t0+av n +b(v-c/c) v>c
t= link travel time per length unit
t 0 =free-flow travel time
v=link flow
c=link capacity
a, b, and n are model (calibrated) parameters
9.3 Model improvement
About all discussed thus far, including the assumptions and limitations, there is always room for improvement for FSM to generate more accurate results. Since transportation dynamics in urban and regional areas are under the complex influence of various factors, the existing models may not be able to incorporate all of them. These can be employer-based trip reduction programs, walking and biking improvement schemes, a shift in departure (time of the day), or more detailed information on socio-demographic and land-use-related factors. However, incorporating some of these variables is difficult and requires minor or significant modifications to the model and/or computational capacities or software improvements. The following section identifies some areas believed to improve the FSM model performance and accuracy.
- Better data: A good way of improving the model accuracy is to gather a complete dataset that represents the general characteristics of the population and travel pattern. If the data is out-of-date or incomplete, we will get poor results.
- Better modal split: As you saw in previous sections, the only modes we incorporate in our model are private car and public transit trips, while in some cities, a considerable fraction of trips are made by bicycle or by walking. We can improve our models by coming up with methods to consider these trips in the first and third steps.
- Auto occupancy: In contemporary transportation planning practices, especially in the US, some new policies are emerging for carpooling. We can calculate auto occupancy rates using different mode types, such as carpooling, sensitive to private car trips’ disutility, parking costs, or introducing a new HOV lane.
- Time of the day: In this chapter, the FSM framework we discussed is more oriented toward peak hour (single time of the day) travel patterns. Nonetheless, understanding the nature of congestion in other hours of the day is also needed to realize how travelers choose their travel time.
- A broader trip purpose: Additional trip purposes may provide a better understanding of the factors affecting different trip purposes and trip-chaining behaviors. We can improve accuracy by having more trip purposes (more disaggregate input and output for the model).
- The concept of access: As discussed, land-use policies that encourage public transit use or create amenities for more convenient walking is not present in the model. Developing factors or indices that reflect such improvements in areas with high demand for non-private vehicles and incorporating them in choice models can be a good improvement.
- Land use feedback: For a better understanding of interactions between land use and travel demand, a land-use simulation model can be added to these steps to determine how a proposed transportation change will lead to a change in land use.
Intersection delays: as mentioned in the fourth step, intersections in major highways create significant delays. Incorporating models that calculate delays at these intersections, such as stop signs, could be another improvement to the model.
9.4 A Simple Example of the FSM model
An example of FSM is provided in this chapter section to illustrate a typical application of this model in the U.S. In the first phase, the data about the transportation network specifications and demographic information about a household are needed. In this hypothetical example, 5 percent of households in each TAZ were sampled and surveyed, which generated 1955 trips in 200 households. As mentioned, this is a hypothetical case study; otherwise, this sample is below the standard needed for statistical significance.
A survey was administered among five percent sample of households for each TAZ in a city. The survey recorded 1852 total trips in the 200 households. (Please note that the sample size in this example is below the minimum category count required for statistical significance as this example is designed for learning purposes only). Table 9.3 shows the network information regarding the speed limit, lanes, and capacity. In Table 9.4, we have information about the distribution of households and different categories of jobs for each zone. Table 9.5 presents the socio-economic information needed for FSM gathered from the surveys.
Source: McNally, 2007
In the first step (trip generation), a category model (i.e., cross-classification) helped estimate trips. The sampled population’s sociodemographic and trip data for different purposes helped calculate this estimate. Since research has shown the significant effect of auto ownership on private car trip-making (Ben-Akiva & Lerman, 1974), disaggregating the population based on the number of private cars generates accurate results. Table 9.7 shows the trip-making rate for different income and auto ownership groups.
Source: adapted from McNally, 2007
Also, as mentioned in previous sections, we can use multiple regression estimation analysis to generate the results for the attraction model. Table 9.7 shows the equations for each of the trip purposes.
After estimating production and attraction, the models are used for population data to generate results for the first step. Next, comparing the results of trip production and attraction, we can observe that the total number of trips for each purpose is different. This can be due to using different methods for production and attraction. Since the production method is more reliable, we usually normalize attraction according to production. Also, some external zones in our study area are either attracting trips from our zones or generating them. In this case, another alternative is to extend the boundary of the study area and include more zones.
As mentioned, the total number of trips produced and attracted are different in these results. To address this mismatch, we can use a balance factor to come up with the same trip generation and attraction numbers if we want to keep the number of zones within our study area. Alternatively, we can consider some external stations in addition to designated zones. In this example, using the latter seems more rational because, as we saw in Table 9.4, there are more jobs than the number of households aggregately, and our zone may attract trips from external locations.
For the trip distribution step, we use the gravity model.
For internal trips, the gravity model is:
T ij = a i b j P i A j f(t ij )
a i = [Σ j b j A j f(t ij )]-1
b j = [Σ i a i P i f(t ij )]-1
and f(tij) is some function of network level of service (LOS)
To apply the gravity model, we need to calculate the impedance function first, which is represented here by travel cost. Table 9.9 shows the minimum travel path between each pair of zones ( skim tree ).
Table 9.9-Travel cost table (skim tree)
With having minimum travel costs between each pair of zones, we can calculate the impedance function for each trip purpose using the formula
f(t ij ) = a t ij .b. exp(ct ij )
Table 9.10 shows the model parameters for calculating the impedance function for different trip purposes:
After calculating the results of the impedance function, we can calculate the result of the trip distribution. This stage generates trip matrices since we calculate trips between each zone pair. These matrices are usually in Origin-Destination (OD) format and can be disaggregated by the time of day. Field surveys help us develop a base-year trip distribution for different periods and trip purposes. Later, these empirical results will help forecast trip distribution. When processing the surveys, the proportion of trips from the production zone to the attraction zone is also generated. This example can be seen in Table 9.11.
Table 9.11 Trip distribution rates for different time of the day and trip purposes
The O-D trip table is calculated by adding the multiplication of the P-to-A factor by corresponding cell of the P-A trip table and adding the corresponding cell of the transposed P-A trip table multiplied by the A-to-P factor. These results, which are the final output of second step, are shown in Table 9.12.
After converting the P-A table to O-D format, and calculating the complete O-D matrix, the results will be aggregated for mode choice and traffic assignment modeling. These two steps will be elaborated in Chapters 11 and 12.
9.5 Issues of FSM
As we saw in this chapter, FSM creates a sequential process for analyzing different type of input data to forecast travel demand at a disaggregate level. However, there are some limitations associated with this modeling framework that has been mentioned by different scholars. Failure to take into account the effects of built environment factors on travel behavior is one big shortcoming of FSM. These factors can be land use pattern, transport network type and design, density, walkability and so on (Mladenovic & Trifunovic, 2014). For instance, vehicle ownership and income as two sociodemographic factors are used to predict travel behavior, but the impact of these built environment factors are absent. Ewing & Cervero (2010) are famous scholars for their conceptualization of built environment in urban planning and transportation studies. Density, Diversity, design, destination accessibility and distance to transit are “5D” variables that represent built environment. All of these variables affect our choice of travel, our choice of residential location and also our share of benefits and burdens of transportation improvements. For instance, the results of an travel forecasting model may suggest increasing surface road capacities by highway extensions to improve overall job accessibility in a region. However, extending a highway through a dense neighborhood may increase exposure rate of residents to pollution, induce land price and relocate them. Such types of project outputs are usually abandoned in FSM modeling, which can lead to serious environmental justice issues. In fact as we saw, in many cities across the county, racial minorities and low-income population cluster in proximity to central city for better access to jobs with low transportation costs in a dense area which is also well-served by transit services to avoid relying on private auto for mobility needs (Kneebone & Berube, 2013). That said, no FSM model takes into account the impact of built environment on such decisions, which are subjects of several transportation equity studies. A result of putting all the faith in these type of model has been isolation and segregation of various vulnerable people and imposition of additional travel costs to them (Karner et al., 2020).
In recent years, some attempts has been made to account for different population groups’ capabilities (such as physical limitation or education) when modeling travel demand and accessibility. However, none of these new improvements have been embedded in FSM framework on a regional level in practice (Pan et al., 2020; Sharifiasl et al., 2023; Shen, 1998). One the other hand, population’s travel behavior modeling has been updated with the choice of activity-based models (ABM), in which various considerations that affect decisions has been added. Some of these additions are having households instead of TAZs as the unit of analysis, modeling tours (a chain of trip such as home to children’s school, school to work, work to shopping, shopping to school and school to home) instead of a single trip, or modeling long term choices (such as home location or auto ownership rate). While these improvements increase modeling reliability by a great deal, much research still is needed to show if utilizing activity-based type models improve transportation equity in the long run compared to FSM.
Travel demand modeling are models that predicts the flow of traffic or travel demand between zones in a city using a sequence of steps.
Intermodality refers to the concept of utilizing two or more travel modes for a trip such as biking to a transit station and riding the light rail.
Multimodality is a type of transportation network in which a variety of modes such as public transit, rail, biking networks, etc. are offered.
Zoning ordinances is legal categorization of land use policies that permits or prohibits certain built environment factors such as density.
Volume capacity ratio is ratio that divides the demand on a link by the capacity to determine the level of service.
Zone centroid is usually the geometric center of a zone in modeling process where all trips originate and end.
Home-based work trips (HBW) are the trips that originates from home location to work location usually in the AM peak.
- Home-based other (or non-work) trips (HBO) are the trips that originates from home to destinations other than work like shopping or leisure.
Non-home-based trips (NHB) are the trips that neither origin nor the destination are home or they are part of a linked trip.
Cross-classification is a method for trip production estimation that disaggregates trip rates in an extended format for different categories of trips like home-based trips or non-home-based trips and different attributes of households such as car ownership or income.
Generalized travel costs is a function of time divided into sections such as in vehicle time vs. waiting time or transfer time in a transit trip.
Binary logit models is a type of logit model where the dependent variable can take only a value of 0 or 1.
Wardrop equilibrium is a state in traffic assignment model where are drivers are reluctant to change their path because the average travel time is at a minimum.
All-or-nothing (AON) assignment model is a model that assumes all trips between two zones uses the shortest path regardless of volume.
Speed flow relationship is a function that determines the speed based on the volume (flow)
skim tree is structure of travel time by defining minimum cost path for each section of a trip.
Key Takeaways
In this chapter, we covered:
- What travel demand modeling is for and what the common methods are to do that.
- How FSM is structured sequentially, what the relationships between different steps are, and what the outputs are.
- What the advantages and disadvantages of different methods and assumptions in each step are.
- What certain data collection and preparation for trip generation and distribution are needed through a hypothetical example.
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How do airplanes fly? An aerospace engineer explains the physics of flight
Professor of Mechanical and Aerospace Engineering, Clarkson University
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Craig Merrett receives funding from the Office of Naval Research and L3Harris. He is affiliated with the American Institute for Aeronautics and Astronautics, and is a licensed professional engineering in Ontario, Canada. Dr. Merrett is an associate professor in the Department of Mechanical and Aerospace Engineering at Clarkson University, Potsdam, NY.
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How do airplanes fly? – Benson, age 10, Rockford, Michigan
Airplane flight is one of the most significant technological achievements of the 20th century. The invention of the airplane allows people to travel from one side of the planet to the other in less than a day, compared with weeks of travel by boat and train.
Understanding precisely why airplanes fly is an ongoing challenge for aerospace engineers, like me , who study and design airplanes, rockets, satellites, helicopters and space capsules.
Our job is to make sure that flying through the air or in space is safe and reliable, by using tools and ideas from science and mathematics, like computer simulations and experiments.
Because of that work, flying in an airplane is the safest way to travel – safer than cars, buses, trains or boats. But although aerospace engineers design aircraft that are stunningly sophisticated, you might be surprised to learn there are still some details about the physics of flight that we don’t fully understand.
May the force(s) be with you
There are four forces that aerospace engineers consider when designing an airplane: weight, thrust, drag and lift. Engineers use these forces to help design the shape of the airplane, the size of the wings, and figure out how many passengers the airplane can carry.
For example, when an airplane takes off, the thrust must be greater than the drag, and the lift must be greater than the weight. If you watch an airplane take off, you’ll see the wings change shape using flaps from the back of the wings. The flaps help make more lift, but they also make more drag, so a powerful engine is necessary to create more thrust.
When the airplane is high enough and is cruising to your destination, lift needs to balance the weight, and the thrust needs to balance the drag. So the pilot pulls the flaps in and can set the engine to produce less power.
That said, let’s define what force means. According to Newton’s Second Law , a force is a mass multiplied by an acceleration, or F = ma.
A force that everyone encounters every day is the force of gravity , which keeps us on the ground. When you get weighed at the doctor’s office, they’re actually measuring the amount of force that your body applies to the scale. When your weight is given in pounds, that is a measure of force.
While an airplane is flying, gravity is pulling the airplane down. That force is the weight of the airplane.
But its engines push the airplane forward because they create a force called thrust . The engines pull in air, which has mass, and quickly push that air out of the back of the engine – so there’s a mass multiplied by an acceleration.
According to Newton’s Third Law , for every action there’s an equal and opposite reaction. When the air rushes out the back of the engines, there is a reaction force that pushes the airplane forward – that’s called thrust.
As the airplane flies through the air, the shape of the airplane pushes air out of the way. Again, by Newton’s Third Law, this air pushes back, which leads to drag .
You can experience something similar to drag when swimming. Paddle through a pool, and your arms and feet provide thrust. Stop paddling, and you will keep moving forward because you have mass, but you will slow down. The reason that you slow down is that the water is pushing back on you – that’s drag.
Understanding lift
Lift is more complicated than the other forces of weight, thrust and drag. It’s created by the wings of an airplane, and the shape of the wing is critical; that shape is known as an airfoil . Basically it means the top and bottom of the wing are curved, although the shapes of the curves can be different from each other.
As air flows around the airfoil, it creates pressure – a force spread out over a large area. Lower pressure is created on the top of the airfoil compared to the pressure on the bottom. Or to look at it another way, air travels faster over the top of the airfoil than beneath.
Understanding why the pressure and speeds are different on the top and the bottom is critical to understand lift . By improving our understanding of lift, engineers can design more fuel-efficient airplanes and give passengers more comfortable flights.
The conundrum
The reason why air moves at different speeds around an airfoil remains mysterious, and scientists are still investigating this question.
Aerospace engineers have measured these pressures on a wing in both wind tunnel experiments and during flight. We can create models of different wings to predict if they will fly well. We can also change lift by changing a wing’s shape to create airplanes that fly for long distances or fly very fast.
Even though we still don’t fully know why lift happens, aerospace engineers work with mathematical equations that recreate the different speeds on the top and bottom of the airfoil. Those equations describe a process known as circulation .
Circulation provides aerospace engineers with a way to model what happens around a wing even if we do not completely understand why it happens. In other words, through the use of math and science, we are able to build airplanes that are safe and efficient, even if we don’t completely understand the process behind why it works.
Ultimately, if aerospace engineers can figure out why the air flows at different speeds depending on which side of the wing it’s on, we can design airplanes that use less fuel and pollute less.
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Can You Work As An Engineer And Travel Full Time?
Read a summary or generate practice questions using the INOMICS AI tool
Remote work can save you $7000 a year because of not having to spend so much on commuting, food, clothing and childcare. Many 'location independent' workers decide to spend this saved money on travel, since they are able to work from anywhere and have always wanted to see more of the world. Does this sound like your dream job? The problem is that not all jobs can be done remotely. Luckily for you, however, engineering work absolutely can. Demand for trained engineers is increasing , and companies know they can cut costs and increase output and employee retention by offering remote work. You just have to know how to find it.
Which Kind Of Engineering Do You Do?
All engineering jobs can be done remotely, but you may want to tailor your training towards in-demand jobs. For instance, software engineering is most commonly done from home, and tech jobs are particularly in demand. Take a look at your skills, and see how you can build on them to match what the market is currently looking for.
Preparing Your Traveling Business
If you're ready to leave the office and hit the road, then you need to set yourself up for success. Get yourself a fast and powerful laptop , a new smartphone for contacting clients, and a decent backpack. Having the right tools is the first step in ensuring you can work efficiently. You can then decide which country you want to travel to, balancing strong infrastructure with low living costs. A suitable vehicle will enable you to travel further and for longer so that you can go to the places that make the most sense as a traveling engineer. Be sure to choose a vehicle that will accommodate all your equipment without infringing on passenger space so that you can use it for leisure time too.
Finding Remote Work
Once you have the training and the tools for becoming a traveling worker, all that is left to do is find the work. Sign up to some reputable remote work websites and start applying to jobs. You will get plenty of rejections, but if you have the experience then eventually someone will hire you. There is far more demand for remote engineers than supply, so it is only a matter of time until you land your dream job.
Engineering is a great way to earn an income, but you may be craving the freedom of life on the move. Fortunately, your skills are highly sought after. Train yourself in the most in-demand forms of engineering, and then prepare yourself for a traveling lifestyle. After this, you will be ready to start accepting location independent engineering gigs.
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From an Engineer’s Standpoint: Why I Travel
It doesn’t matter if it’s for work or for play. Just go out there!
It’s pretty normal for engineers, especially among millennials, to have this desire to travel or what they call as wanderlust. If you’re lucky, it could be part of the work; but in most cases it’s just a way to take a break.
I am no longer surprised that my engineer friends are incessantly checking for cheap ticket fares and booking themselves a trip when there’s a chance on weekends and holidays. Because I’m guilty of that as well, as a form of releasing my stress at work.
But what most engineers do not realize is that regardless if traveling is a part of the job or a vacation, it is certainly a part of the growth as a professional.
These reasons below should convince you how:
Rejuvenation of one’s being
In general, people travel as a diversion from the repetitive and routine work. But it’s different in engineering, where we face numbers and technical matters on a daily basis.
So when we get to experience things and meet new people, we feel refreshed. It is an escape from the everyday stress at work. We realize upon ourselves that there is a whole lot to do out there to nourish our souls and not only to become a slave of our engineering jobs.
There is a different world outside of the laboratory, construction site, and offices waiting to be enjoyed. And the only that you could meet is if you travel.
New relationships, new perspectives
Along the course of an engineer’s travel, he or she can meet people who are willing to engage in short but life-changing talks, which enhance his or her understanding about the world and its diversity of cultures.
The new people you encounter, despite the short-lived relationships you make with them, contribute to your perspective about life at a certain depth. Their stories provide a perspective that can change you for the better as a person.
Appreciation of the engineering profession
Traveling puts some engineers into a position that will make them appreciate what’s present and absent back where they originate, especially on things related to the field.
Case in point: I’m a civil engineer and when I got to see a bigger city that is 300 kilometers away where I am from, I had a clearer vision of urban infrastructure and different modes of transportation.
Better communication skills
Nobody ever survives an out-of-town trip without ever having to speak to a local for directions.
More often than not, there are language barriers, and that’s where the fun and learning of travel begins. Engineers are supposed to overcome this by listening and through non-verbal skills. One can practice this by traveling more. Later on, this acquired skill can further be applied on the job.
Personal fulfilment
Some just like to travel for the sole purpose of ticking off that bucket list. Just to have fun. And to live outside their comfort zones.
Engineers gain personal fulfilment through traveling. When you have an itchy feet like me, you would know that staying in one place means a slow death.
J.R.R. Tolkien could never say it better: not all who wander are lost.
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A Guide to the Most Beautiful Green Spaces in Moscow
Home to more parks than any other city in Russia , Moscow offers a cornucopia of choice when it comes to green spaces. From innovative wild urbanism to 18th-century royal estates, here are the best places to escape from the city buzz in Russia’s capital.
Spread over a territory of almost 300 acres, Gorky Park is Moscow’s most popular green space. Opened in 1928, it was designed as ‘a city inside a city’ with its own telegraph, police unit and a doctor’s office. Some 90 years later, Gorky Park offers everything from segway rides to an open-air movie theatre, through to illuminating lectures and fantastic dining spots.
9 Krimsky Val, Moscow, Russia , +7 495 995 00 20
As the name implies, Muzeon is perfect for art lovers. The park plays host to art fairs, exhibitions, music festivals and video performances. But even if you don’t care for art, Muzeon has a lot to offer: from an elegant boardwalk to hip coffee shops to an in-ground fountain, where you can actually cool off in summer.
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2 Krimsky Val, Moscow, Russia , +7 985 382 27 32
Hermitage Garden
Opened in 1894, the Hermitage garden is a lovely compact park, nestled between high rise buildings in Moscow center. Home to theaters New Opera, Hermitage and Sphera, the garden is predictably crowded, with theatre-goers along with office workers from the business centres in Tverskaya – all flock here for a green respite.
3 Karetnyy Ryad, Moscow, Russia , +7 495 699 04 32
Sokolniki Park
An open-air cinema, a rope course, amusement park, bike rentals and more – Sokolniki is 1,275 acres of fun. In winter the whole park turns into one of Moscow’s most famous skating rinks. Sokolniki gradually blends into Losiny Ostrov National Park – the world’s third largest forest in a city.
1 Sokol’nicheskiy Val, bld. 1, Moscow, Russia , +7 499 393 92 22
Izmailovsky Park
Moscow’s biggest park, Izmailovsky stretches for almost 3,800 acres. Particularly favored by hikers and cyclists, the forest-like park is a popular family spot, equipped with a ferris wheel, outdoor gyms and all kinds of places to eat.
7 Alleya Bol’shogo Kruga, Moscow, Russia , +7 499 166 61 19
Tsaritsyno Museum-Reserve
Tsaritsyno estate is a perfectly reconstructed specimen of 18th century architecture set amid a lush green forested area. The only park in Moscow that boasts a light and music fountain, Tsaritsyno draws crowds with spectacular night water shows.
1 Dol’skaya Ulitsa, Moscow, Russia , +7 499 725 72 87
Severnoye Tushino Park
Despite a rather remote location, this park is definitely worth a visit. A half-a-century old apple garden, serene views on Khimkinskoye reservoir and a dry-docked submarine housing a Museum of Submarine Navy will definitely make up for the ride from the city centre.
Ulitsa Svobody, Moscow, Russia , +7 495 640 73 55
Kolomenskoye
Kolomenskoye Park is not merely a tranquil green space, but a celebrated museum reserve, where nature and historically significant architecture blend together. Here you can see one of Moscow’s oldest churches Church of the Ascension and a former residence of the Tsar Aleksey Mikhailovich Romanov, the father of Peter the Great. It’s also perfect for romantic walks along the Moskva river.
39 Andropova Ave, Moscow, Russia , +7 499 782 89 17
In this park you’re guaranteed to encounter some ducks, woodpeckers, squirrels, hares and urban wildlife. The park is also famous for its beautiful boardwalk, open-air cinema, ropes course Panda Park, gallery of retro cars and a variety of places to eat.
22/1 Ulitsa Bol’shaya Filevskaya, Moscow, Russia , +7 499 145 45 05
The former estate of the Sheremetev family, Kuskovo is a fascinating piece of 18th-century Russia. Home to 20 unique architectural monuments, it is Moscow’s only historical park with a French formal garden, decorated with green walkways, marble statue and state-of-the art pavilions.
44/2 3-Ya Muzeynaya Ulitsa, Moscow, Russia
KEEN TO EXPLORE THE WORLD?
Connect with like-minded people on our premium trips curated by local insiders and with care for the world
Since you are here, we would like to share our vision for the future of travel - and the direction Culture Trip is moving in.
Culture Trip launched in 2011 with a simple yet passionate mission: to inspire people to go beyond their boundaries and experience what makes a place, its people and its culture special and meaningful — and this is still in our DNA today. We are proud that, for more than a decade, millions like you have trusted our award-winning recommendations by people who deeply understand what makes certain places and communities so special.
Increasingly we believe the world needs more meaningful, real-life connections between curious travellers keen to explore the world in a more responsible way. That is why we have intensively curated a collection of premium small-group trips as an invitation to meet and connect with new, like-minded people for once-in-a-lifetime experiences in three categories: Culture Trips, Rail Trips and Private Trips. Our Trips are suitable for both solo travelers, couples and friends who want to explore the world together.
Culture Trips are deeply immersive 5 to 16 days itineraries, that combine authentic local experiences, exciting activities and 4-5* accommodation to look forward to at the end of each day. Our Rail Trips are our most planet-friendly itineraries that invite you to take the scenic route, relax whilst getting under the skin of a destination. Our Private Trips are fully tailored itineraries, curated by our Travel Experts specifically for you, your friends or your family.
We know that many of you worry about the environmental impact of travel and are looking for ways of expanding horizons in ways that do minimal harm - and may even bring benefits. We are committed to go as far as possible in curating our trips with care for the planet. That is why all of our trips are flightless in destination, fully carbon offset - and we have ambitious plans to be net zero in the very near future.
A Guide to Cautionary Russian Proverbs and What They Mean
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Backlash (engineering) In mechanical engineering, backlash, sometimes called lash, play, or slop, is a clearance or lost motion in a mechanism caused by gaps between the parts. It can be defined as "the maximum distance or angle through which any part of a mechanical system may be moved in one direction without applying appreciable force or ...
The spring or weight travel, however, limits the amount of rotation of the last gear. ... Setting the Agricultural Industry in Motion. Feb. 22, 2024 ... CAD/CAM Roundup: Engineering Software ...
The Importance of Fit, Tolerance & Clearance. Many equipment breakdowns and stoppages occur because of improper clearance between holes and shafts. The shaft is too tight in the hole; the center of the hole is not at the center of the shaft making it off-center; one part is loose on another and slips out of place or does not seal as it should.
that they function correctly (such as setting working clearance, setting travel, setting backlash in gears, preloading bearings) 22. the importance of making `off-load' checks before running the equipment under power 23. the importance of completing maintenance documentation and/or reports following the maintenance activity 24.
This standard identifies the competences you need to carry out corrective maintenance activities on mechanical equipment, in accordance with approved procedures. This will involve dismantling, removing and replacing or repairing faulty components, in line with company procedures, on a variety of different types of mechanical equipment such as ...
Engineering tolerance is the permissible variation in measurements deriving from the base measurement. Tolerances can apply to many different units. For example, the working conditions may have tolerances for temperature (° C), humidity (g/m 3 ), etc. In mechanical engineering, we are mainly talking about tolerances that apply to linear ...
A group of vehicles typically do not travel at the exact same speed; thus a speed study usually creates a speed distribution. With an engineering approach, a speed study is done for a specific road segment during a certain period of time for a specific sample set to determine mean speed and the speed distribution.
3.4: Trip Generation. Trip Generation is the first step in the conventional four-step transportation forecasting process (followed by Destination Choice, Mode Choice, and Route Choice), widely used for forecasting travel demands. It predicts the number of trips originating in or destined for a particular traffic analysis zone.
This study focuses on master's-level transportation engineering curricula, with the goal of investigating how changes in employment opportunities and day-to-day work responsibilities of transportation engineers over the coming 5-10 years will inform the topics that graduate-level curricula should include to set students up for future success.
Manufacturing and Engineering Sector and is part of an overall development programme designed to meet the requirements of the Sector. ... setting travel, setting backlash in gears, preloading bearings) K22 Explain the importance of making 'off-load' checks before running the equipment
Traffic calming is a physical alternation implemented either based on engineering strategies or when speed is identified as a problem. Speed management countermeasures consist of horizontal, vertical, lane narrowing, roadside, and other features that use physical or psycho-perception means to produce desired effects.
Avoid distance. This setting defines the distance (in mm) between the nozzle and the print when avoid already printed parts is enabled. A greater avoid distance means a reduced chance of contact with the printed model, however a large avoid distance will significantly affect the length of the travel moves, impacting the print time, and chance ...
4 Level 2 NVQ Diploma in Performing Engineering Operations unit 019 continued on page 5 Evidence reference number Evidence reference number Evidence reference number ... setting working clearance, setting travel, setting backlash in gears, preloading bearings). continued on page 9. Unit 019 Maintaining mechanical devices and equipment 9 ...
9 Chapter 9: Introduction to Transportation Modeling: Travel Demand Modeling and Data Collection . Abstract. Chapter 9 is the prelude to travel demand modeling, an essential task in transportation planning and policy analysis. As discussed in previous chapters, the spatial distribution of activities like jobs, residents, and transportation systems have mutual impacts on each other.
1.2 ensure the safe isolation of equipment (such as mechanical, electrical, gas, air or fluids), where appropriate. 1.3 follow job instructions, maintenance drawings and procedures. 1.4 check that the tools and test instruments are within calibration date, and are in a safe and usable condition. 1.5 ensure that the system is kept free from ...
With sleek "ogival delta" wings, high aspect ratio, and advanced engines, the Concorde cruised at Mach 2.04, more than twice the speed of sound, revolutionizing air travel and setting numerous ...
Go into quality engineering. Lots of travel opportunities. Traveling for work is neat, but unless you can figure out a way to stay in one spot for an extended period of time its typically a fly in fly out week which leaves little time for 'seeing the sites.'. Field and sales engineering does this to a good extent.
The forces of weight, thrust, drag and lift act on a plane to keep it aloft and moving. NASA May the force(s) be with you. There are four forces that aerospace engineers consider when designing an ...
The ideological motivation, "welfare of the masses," was the pertinent design philosophy for designing public spaces in transit hub. Many factors contribute to the success of underground public spaces in Moscow. Decent year-round thermal comfort is one of the reasons for the success.
Travels. engineering. Remote work can save you $7000 a year because of not having to spend so much on commuting, food, clothing and childcare. Many 'location independent' workers decide to spend this saved money on travel, since they are able to work from anywhere and have always wanted to see more of the world.
The 48-floor, 169,000 square meter project is set to include office space, a shopping center, underground parking, a wedding palace, and the Museum of the International Business Center. The Evolution Tower has a unique DNA-like double-helix design in Moscow's new central business district. Read about Arup's 3D modelling projects and engineering ...
Rejuvenation of one's being. In general, people travel as a diversion from the repetitive and routine work. But it's different in engineering, where we face numbers and technical matters on a daily basis. So when we get to experience things and meet new people, we feel refreshed. It is an escape from the everyday stress at work.
Izmailovsky Park. Moscow's biggest park, Izmailovsky stretches for almost 3,800 acres. Particularly favored by hikers and cyclists, the forest-like park is a popular family spot, equipped with a ferris wheel, outdoor gyms and all kinds of places to eat. 7 Alleya Bol'shogo Kruga, Moscow, Russia, +7 499 166 61 19.
Philip Nikandrov, the chief architect, believes that the initial design of the Tower, revealed in 2004, set off a wave of imitators. It took 12 years to go from design to handover. Philip says :