Trip generation

Last updated

Trip generation is the first step in the conventional four-step transportation forecasting process used for forecasting travel demands. It predicts the number of trips originating in or destined for a particular traffic analysis zone (TAZ). [1] Trip generation analysis focuses on residences and residential trip generation is thought of as a function of the social and economic attributes of households. At the level of the traffic analysis zone, residential land uses "produce" or generate trips. Traffic analysis zones are also destinations of trips, trip attractors. The analysis of attractors focuses on non-residential land uses.

Contents

This process is followed by trip distribution, mode choice, and route assignment.

Input data

A forecasting activity, 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 in a disaggregate-spatial manner among zones. The next step in the transportation planning process addresses the question of the frequency of origins and destinations of trips in each zone: for short, trip generation.

Analysis

Initial analysis

The first zonal trip generation (and its inverse, attraction) analysis in the Chicago Area Transportation Study (CATS) [2] followed the “decay of activity intensity with distance from the central business district (CBD)” thinking current at the time. Data from extensive surveys were arrayed and interpreted on a distance-from-CBD scale. For example, commercial land use in ring 0 (the CBD and vicinity) was found to generate 728 vehicle trips per day in 1956. That same land use in ring 5 (about 17 km (11 mi) from the CBD) generated about 150 trips per day.

The case of trip destinations will illustrate use of the concept of activity decline with intensity (as measured by distance from CBD) worked. Destination data are arrayed:

Table: Trip Destinations per unit (Acre) of Land
RingManufacturingCommercialOpen Spaceetc.
0x1mx1cx1osx1n
7x7mx7cx7osx7n

The land use analysis provides information on how land uses will change from an initial year (say t = 0) to some forecast year (say t = 20). Suppose we are examining a zone. We take the mix of land uses projected, say, for year t = 20 and apply the trip destination rates for the ring in which the zone is located. That is, there will this many acres of commercial land use, that many acres of public open space, etc., in the zone. The acres of each use type are multiplied by the ring specific destination rates. The result is summed to yield the zone’s trip destinations. The CATS assumed that trip destination rates would not change over time.

Revisions to the analysis

As was true for land use analysis, the approach developed at CATS was considerably modified in later studies. The conventional four-step paradigm evolved as follows: Types of trips are considered. Home-based (residential) trips are divided into work and other, with major attention given to work trips. Movement associated with the home end of a trip is called trip production, whether the trip is leaving or coming to the home. Non-home-based or non-residential trips are those a home base is not involved. In this case, the term production is given to the origin of a trip and the term attraction refers to the destination of the trip.

Residential trip generation analysis is often undertaken using statistical regression. Person, transit, walking, and auto trips per unit of time are regressed on variables thought to be explanatory, such as: household size, number of workers in the household, persons in an age group, type of residence (single family, apartment, etc.), and so on. Usually, measures on five to seven independent variables are available; additive causality is assumed.

Regressions are also made at the aggregate/zone level. Variability among households within a zone isn’t measured when data are aggregated. High correlation coefficients are found when regressions are run on aggregate data, about 0.90, but lower coefficients, about 0.25, are found when regressions are made on observation units such as households. In short, there is much variability that is hidden by aggregation.

Sometimes cross-classification techniques are applied to residential trip generation problems. The CATS procedure described above is a cross-classification procedure.

Classification techniques are often used for non-residential trip generation. First, the type of land use is a factor influencing travel, it is regarded as a causal factor. A list of land uses and associated trip rates illustrated a simple version of the use of this technique:

Table: Trips per day
Land Use TypeTrips
Department StoreX
Grocery StoreY

Such a list can be improved by adding information. Large, medium, and small might be defined for each activity and rates given by size. Number of employees might be used: for example, <10, 10-20, etc. Also, floor space is used to refine estimates.

In other cases, regressions, usually of the form trip rate = f(number of employees, floor area of establishment), are made for land use types.

Special treatment is often given major trip generators: large shopping centers, airports, large manufacturing plants, and recreation facilities.

The theoretical work related to trip generation analysis is grouped under the rubric travel demand theory, which treats trip generation-attraction, as well as mode choice, route selection, and other topics.

Databases

The Institute of Transportation Engineers's Trip Generation Manual provides trip generation rates for various land use and building types. The planner can add local adjustment factors and treat mixes of uses with ease. Ongoing work is adding to the stockpile of numbers; over 4000 studies were aggregated for the latest edition.

ITE Procedures estimate the number of trips entering and exiting a site at a given time. ITE Rates are functions of type of development based on independent variables such as square footage of the gross leasable area, number of gas pumps, number of dwelling units, or other standard measurable things, usually produced in site plans. [3] They are typically of the form or . They do not consider location, competitors, complements, the cost of transportation, or other factors. The trip generation estimates are provided through data analysis. Many localities require their use to ensure adequate public facilities for growth management and subdivision approval.

In the United Kingdom and Ireland, the TRICS database is commonly used to calculate trip generation.

Related Research Articles

Transportation engineering Academic discipline and occupational field

Transportation engineering or transport engineering is the application of technology and scientific principles to the planning, functional design, operation and management of facilities for any mode of transportation in order to provide for the safe, efficient, rapid, comfortable, convenient, economical, and environmentally compatible movement of people and goods transport.

Transportation planning Process of planning for movement of people and goods

Transportation planning is the process of defining future policies, goals, investments, and spatial planning designs to prepare for future needs to move people and goods to destinations. As practiced today, it is a collaborative process that incorporates the input of many stakeholders including various government agencies, the public and private businesses. Transportation planners apply a multi-modal and/or comprehensive approach to analyzing the wide range of alternatives and impacts on the transportation system to influence beneficial outcomes.

Parking Act of stopping and disengaging a vehicle and usually leaving it unoccupied

Parking is the act of stopping and disengaging a vehicle and leaving it unoccupied. Parking on one or both sides of a road is often permitted, though sometimes with restrictions. Some buildings have parking facilities for use of the buildings' users. Countries and local governments have rules for design and use of parking spaces.

A prediction, or forecast, is a statement about a future event or data. They are often, but not always, based upon experience or knowledge. There is no universal agreement about the exact difference from "estimation"; different authors and disciplines ascribe different connotations.

Travel behavior

Travel behavior is the study of what people do over space, and how people use transport.

Concentric zone model

The concentric zone model, also known as the Burgess model or the CCD model, is one of the earliest theoretical models to explain urban social structures. It was created by sociologist Ernest Burgess in 1925.

A traffic analysis zone or transportation analysis zone (TAZ) is the unit of geography most commonly used in conventional transportation planning models. The size of a zone varies, but for a typical metropolitan planning software, a zone of under 3,000 people is common. The spatial extent of zones typically varies in models, ranging from very large areas in the exurb to as small as city blocks or buildings in central business districts. There is no technical reason zones cannot be as small as single buildings, however additional zones add to the computational burden.

Trip distribution

Trip distribution is the second component in the traditional four-step transportation forecasting model. This step matches tripmakers’ origins and destinations to develop a “trip table”, a matrix that displays the number of trips going from each origin to each destination. Historically, this component has been the least developed component of the transportation planning model.

Mode choice

Mode choice analysis is the third step in the conventional four-step transportation forecasting model. The steps, in order, are trip generation, trip distribution, mode choice analysis, and route assignment. Trip distribution's zonal interchange analysis yields a set of origin destination tables that tells where the trips will be made. Mode choice analysis allows the modeler to determine what mode of transport will be used, and what modal share results.

Route assignment

Route assignment, route choice, or traffic assignment concerns the selection of routes between origins and destinations in transportation networks. It is the fourth step in the conventional transportation forecasting model, following trip generation, trip distribution, and mode choice. The zonal interchange analysis of trip distribution provides origin-destination trip tables. Mode choice analysis tells which travelers will use which mode. To determine facility needs and costs and benefits, we need to know the number of travelers on each route and link of the network. We need to undertake traffic assignment. Suppose there is a network of highways and transit systems and a proposed addition. We first want to know the present pattern of traffic delay and then what would happen if the addition were made.

Land-use forecasting undertakes to project the distribution and intensity of trip generating activities in the urban area. In practice, land-use models are demand-driven, using as inputs the aggregate information on growth produced by an aggregate economic forecasting activity. Land-use estimates are inputs to the transportation planning process.

In medical research, social science, and biology, a cross-sectional study is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data.

In mathematics and transportation engineering, traffic flow is the study of interactions between travellers and infrastructure, with the aim of understanding and developing an optimal transport network with efficient movement of traffic and minimal traffic congestion problems.

Spatial analysis Formal techniques which study entities using their topological, geometric, or geographic properties

Spatial analysis or spatial statistics includes any of the formal techniques which studies entities using their topological, geometric, or geographic properties. Spatial analysis includes a variety of techniques, many still in their early development, using different analytic approaches and applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures. In a more restricted sense, spatial analysis is the technique applied to structures at the human scale, most notably in the analysis of geographic data or transcriptomics data.

Modifiable areal unit problem Statistical bias encountered when point-based measures of spatial phenomena are aggregated into districts

The modifiable areal unit problem (MAUP) is a source of statistical bias that can significantly impact the results of statistical hypothesis tests. MAUP affects results when point-based measures of spatial phenomena are aggregated into districts, for example, population density or illness rates. The resulting summary values are influenced by both the shape and scale of the aggregation unit.

Transportation forecasting

Transportation forecasting is the attempt of estimating the number of vehicles or people that will use a specific transportation facility in the future. For instance, a forecast may estimate the number of vehicles on a planned road or bridge, the ridership on a railway line, the number of passengers visiting an airport, or the number of ships calling on a seaport. Traffic forecasting begins with the collection of data on current traffic. This traffic data is combined with other known data, such as population, employment, trip rates, travel costs, etc., to develop a traffic demand model for the current situation. Feeding it with predicted data for population, employment, etc. results in estimates of future traffic, typically estimated for each segment of the transportation infrastructure in question, e.g., for each roadway segment or railway station. The current technologies facilitate the access to dynamic data, big data, etc., providing the opportunity to develop new algorithms to improve greatly the predictability and accuracy of the current estimations.

TRANSIMS is an integrated set of tools developed to conduct regional transportation system analyses. With the goal of establishing TRANSIMS as an ongoing public resource available to the transportation community, TRANSIMS is made available under the NASA Open Source Agreement Version 1.3

Walkability Measure of pedestrianism in an area

Walkability is a measure of how friendly an area is for walking. Walkability has health, environmental, and economic benefits. Factors influencing walkability include the presence or absence and quality of footpaths, sidewalks or other pedestrian rights-of-way, traffic and road conditions, land use patterns, building accessibility, and safety, among others. Walkability is an important concept in sustainable urban design. Project Drawdown describes making cities walkable as an important solution in the toolkit for adapting cities to climate change: it reduces carbon emissions, and improves quality of life.

Design of robust and reliable networks and network services relies on an understanding of the traffic characteristics of the network. Throughout history, different models of network traffic have been developed and used for evaluating existing and proposed networks and services.

References

  1. "Trip generation". Transport for London. Retrieved December 18, 2021.
  2. Black, Alan (1990). "The Chicago Area Transportation Study: A Case Study of Rational Planning". Journal of Planning Education and Research. 10 (1). doi:10.1177/0739456X9001000105 . Retrieved December 18, 2021.
  3. "Independent Variables". Institute of Transportation Engineers. Retrieved December 17, 2021.

See also