Case Study in the Application of Adjusted Census Data for Planning Projects

The reasons for differences between locally collected data and the 1990 census data, as determined from a detailed analysis of model development efforts in a planning study, are detailed. Agencies around the country are beginning to use census data that have been adjusted based on newly released Federal Highway Administration publications. The recently completed Transportation Planner’s Handbook on Conversion Factors for the Use of Census Data has been published to assist planners in using the 1990 census to develop and calibrate local travel demand models. Collecting new data to complete the development of a local model is not always an option. The 1990 census provides another source of information to assist in traffic model estimation. Potential users of the census need to be aware that there would appear to be a variance between results obtained from the census journey-to-work files and locally developed home interview surveys, even after the use of the census adjustment factors. The project in Atlanta, Georgia, involved detailed traffic model development and calibration, in conjunction with factor-adjusted census data. Because of the intimate understanding of the data for the study area, and the development of the model set from the beginning, differences between the locally collected data and census were explainable. Possible problems that can arise when comparing the data as they relate to geography, data definition, and accuracy of the data collection process are detailed.

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Population Synthesis for a City in a Developing Country

Periodica Polytechnica Transportation Engineering ◽

10.3311/pptr.14938 ◽

2020 ◽

Author(s):

Devika Babu ◽

Sreelakshmi Balan ◽

Anjaneyulu Matha Venkata Lakshmi Ranga

Keyword(s):

Developing Country ◽

Travel Demand ◽

Developing Economies ◽

Simulated Data ◽

Developed Countries ◽

Population Characteristics ◽

Population Synthesis ◽

Household Level ◽

Demand Models ◽

Home Interview

Activity-based approach in transportation studies increased the demand for detailed disaggregate data. To overcome the tedious and costly data collection, synthesized data are widely used in activity based modeling practices in developed countries. In the case of developing economies, time, resource and monetary constraints hinder the development of new generation travel demand models. Population synthesis practices are the need of the hour in developing countries. Through this study, the authors proposed a method for population synthesis for a medium sized city, in a developing country. Details from 9901 households, collected through home-interview survey in 2011 formed the database for this work. The proposed synthesis procedure makes use of Monte Carlo process along with logit modeling technique to simulate population attributes using the survey data. The procedure is developed as a Visual Basic Application in spreadsheet platform. By adopting this method, various household level and person level attributes are simulated. Comparison of observed data from survey and simulated data showed consistent results and low differences. It is expected that this study will assist the planning authorities to better understand the city′s population characteristics.

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Exploration of Long-Distance Interregional Commuting Issues: Analysis of Northern California Interregional Commuters Using Census Data and Focus Group Interviews

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198196152100104 ◽

1996 ◽

Vol 1521 (1) ◽

pp. 29-36 ◽

Cited By ~ 1

Author(s):

Richard W. Lee

Keyword(s):

Focus Group ◽

Survey Data ◽

Travel Demand ◽

Census Data ◽

Basic Research ◽

Northern California ◽

Single Family ◽

Long Distance ◽

Travel Survey ◽

Demand Models

Recent national and local travel surveys indicate substantial increases in types of travel that are not well explained by most applications of traditional travel demand models. Understanding phenomena such as nonwork travel, the travel patterns of nontraditional households, or long-distance interregional commuting requires new basic research. A promising approach to primary travel demand research was developed and is described. A case study of interregional commuting in Northern California that combined quantitative analysis of census and travel survey data with focus group techniques is presented. Census data provided the basis for defining various types of commuters; the characteristics of these types were then elaborated via the focused interviews including “rolling focus groups” aboard commuter vans. Approximately 40 commuters were interviewed in depth. The interviews illuminated important issues that clarify the census and travel survey data. The findings indicate that an affordable single-family home is the primary motivation of interregional commuters; a variety of personal, household, and schedule adaptations make commuting palatable; and key prerequisites for interregional commuting include a job and lifestyle that permit adherence to a routine. Interregional commuters appear to be good candidates for shared-ride modes.

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Analyzing Cell Phone Location Data for Urban Travel

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2526-14 ◽

2015 ◽

Vol 2526 (1) ◽

pp. 126-135 ◽

Cited By ~ 64

Author(s):

Serdar Çolak ◽

Lauren P. Alexander ◽

Bernardo G. Alvim ◽

Shomik R. Mehndiratta ◽

Marta C. González

Keyword(s):

Travel Behavior ◽

Rio De Janeiro ◽

Cell Phone ◽

Travel Demand ◽

Census Data ◽

Low Cost ◽

Time Of Day ◽

Raw Data ◽

Home Based ◽

Demand Models

Travelers today use technology that generates vast amounts of data at low cost. These data could supplement most outputs of regional travel demand models. New analysis tools could change how data and modeling are used in the assessment of travel demand. Recent work has shown how processed origin–destination trips, as developed by trip data providers, support travel analysis. Much less has been reported on how raw data from telecommunication providers can be processed to support such an analysis or to what extent the raw data can be treated to extract travel behavior. This paper discusses how cell phone data can be processed to inform a four-step transportation model, with a focus on the limitations and opportunities of such data. The illustrated data treatment approach uses only phone data and population density to generate trip matrices in two metropolitan areas: Boston, Massachusetts, and Rio de Janeiro, Brazil. How to label zones as home- and work-based according to frequency and time of day is detailed. By using the labels (home, work, or other) of consecutive stays, one can assign purposes to trips such as home-based work. The resulting trip pairs are expanded for the total population from census data. Comparable results with existing information reported in local surveys in Boston and existing origin–destination matrices in Rio de Janeiro are shown. The results detail a method for use of passively generated cellular data as a low-cost option for transportation planning.

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Creating a Synthetic Household Travel and Activity Survey: Rationale and Feasibility Analysis

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1706-10 ◽

2000 ◽

Vol 1706 (1) ◽

pp. 82-91 ◽

Cited By ~ 17

Author(s):

S. P. Greaves ◽

P. R. Stopher

Keyword(s):

Survey Data ◽

Travel Demand ◽

Model Development ◽

Synthetic Data ◽

Data Set ◽

Travel Survey ◽

Simulation Procedure ◽

Demand Models ◽

Study Results ◽

Household Travel

Proposed is a new approach for developing the travel survey data required for use in local travel-demand models. Using readily available local sociodemographic information in conjunction with a freely available national travel survey, a simulation procedure is described to create, in effect, a synthetic household travel survey. The reasons for interest in such a procedure are outlined, including the costs and difficulties associated with gathering high-quality travel data. Consideration is then given to alternatives for local model development, such as the use of national data averages and borrowed models. The simulation procedure is then described and tested in a region that has recently completed a travel survey; this provides a direct source of comparison of the merit of the approach. Trip production models are then built using the synthetic data set. The case study results show that the synthetic data ( a) offer significant improvements over the use of borrowed models and ( b) estimate new models that are similar to those same models estimated using the local travel survey data. It is concluded that these results show that the approach has considerable promise. Finally, some future directions are described, including the planned extension of the approach to other regions.

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MODEL DISTRIBUSI PERJALANAN PENDUDUK UNTUK PENENTUAN KORIDOR ‘LRT’ DI PULAU BATAM

Jurnal Sains dan Teknologi Indonesia ◽

10.29122/jsti.v12i3.856 ◽

2013 ◽

Vol 12 (3) ◽

Author(s):

Djoko Prijo Utomo

Keyword(s):

Network Performance ◽

Travel Demand ◽

Mass Transit ◽

Distribution Model ◽

Economic Activities ◽

Transit System ◽

Trip Distribution ◽

Home Interview ◽

Interview Survey ◽

Private Car

In consequence of the increasing of regional economic activities in Pulau Batam, a reliable transportation system is required. Decreasing road network performance as a result of increasing traffic volume needs a strategic planning to anticipate the worsening condition in the future. One of the solutions is by providing mass transit system which is expected to attract private car users. Therefore, determination of potential corridor of mass transit system need to be identified so that the system provide better accessibility. Trip pattern in Pulau Batam must be known by developing trip distribution model. The trip distribution model is calibrated using origin-destination (O-D) data that is based on home interview survey. The validated model will be used to forecast and simulate travel demand onto transport network. Result of model calibration process shows mean trip length difference between model and survey is equal 0.141 %. From simulation of trip assignment is obtained that potential corridor for mass transit system using LRT is Batu Ampar – Batu Aji via Muka Kuning. Passenger forecast in the year 2030 is 193,990 passenger/day (2 directions).

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PENGEMBANGAN ”REAL TIME TRAFFIC INFORMATION SYSTEM” BAGI PENGGUNA JALAN

Jurnal Sains dan Teknologi Indonesia ◽

10.29122/jsti.v12i3.861 ◽

2013 ◽

Vol 12 (3) ◽

Author(s):

Rusmadi Suyuti

Keyword(s):

Information System ◽

Real Time ◽

Travel Demand ◽

Urban Traffic ◽

Road User ◽

Traffic Information ◽

Estimation Methods ◽

Traffic Counts ◽

Real Time Traffic ◽

Demand Models

Traffic information condition is a very useful information for road user because road user can choose his best route for each trip from his origin to his destination. The final goal for this research is to develop real time traffic information system for road user using real time traffic volume. Main input for developing real time traffic information system is an origin-destination (O-D) matrix to represent the travel pattern. However, O-D matrices obtained through a large scale survey such as home or road side interviews, tend to be costly, labour intensive and time disruptive to trip makers. Therefore, the alternative of using traffic counts to estimate O-D matrices is particularly attractive. Models of transport demand have been used for many years to synthesize O-D matrices in study areas. A typical example of the approach is the gravity model; its functional form, plus the appropriate values for the parameters involved, is employed to produce acceptable matrices representing trip making behaviour for many trip purposes and time periods. The work reported in this paper has combined the advantages of acceptable travel demand models with the low cost and availability of traffic counts. Two types of demand models have been used: gravity (GR) and gravity-opportunity (GO) models. Four estimation methods have been analysed and tested to calibrate the transport demand models from traffic counts, namely: Non-Linear-Least-Squares (NLLS), Maximum-Likelihood (ML), Maximum-Entropy (ME) and Bayes-Inference (BI). The Bandung’s Urban Traffic Movement survey has been used to test the developed method. Based on several statistical tests, the estimation methods are found to perform satisfactorily since each calibrated model reproduced the observed matrix fairly closely. The tests were carried out using two assignment techniques, all-or-nothing and equilibrium assignment.

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