01478682

Component

https://doi.org/10.3141/2354-08

http://scholar.google.com...andy&publication_year=2013

This study presents a method to quantify multimodal trip generation for developments in smart-growth areas. The technique combines door counts and intercept surveys to classify trips by mode, and it has several advantages over existing methods that use automated technologies to count automobiles entering and exiting access points to developments. These advantages are particularly important in urban areas with mixed-use developments, mixed-use buildings, and a variety of parking arrangements. First, door counts quantify the total number of trips generated by all modes. Second, door counts quantify all people traveling to and from particular land uses, even if a targeted use is part of a larger, mixed-use building. Third, intercept surveys differentiate between people who are walking for an entire trip and people who are walking as a secondary mode to or from parking or transit. The method was applied at 30 smart-growth study locations in California. Multimodal person trips and vehicle trips were documented at 24 of the study locations during the morning peak hour and at 27 study locations during the afternoon peak hour. Weighted averages from these locations show that suburban-based ITE peak hour vehicle trip estimates were 2.3 times higher than actual vehicle trips in the morning and 2.4 times higher than those in the afternoon. Total person trip generation at the smart-growth study locations was similar to the total person trips estimated from ITE data; however, larger shares of person trips at the smart-growth locations were made by walking, bicycling, or public transit.

01496622

13-5108

English

pp 68–85

2013

Transportation Research Record: Journal of the Transportation Research Board

9780309286701

Print

Figures (1) ; References (14) ; Tables (6)

Data collection; Methodology; Modal split; Multimodal transportation; Smart growth; Travel surveys; Trip generation

Institute of Transportation Engineers

Data and Information Technology; Highways; Pedestrians and Bicyclists; Planning and Forecasting; Public Transportation; I21: Planning of Transport Infrastructure; I70: Traffic and Transport

PRP, TRIS, TRB, ATRI

Feb 5 2013 12:58PM

• Application of Geographic Perturbation Methods to Residential Locations in the Oregon Household Activity Survey: Proof of Concept
• Examining Estimation Bias and Efficiency for Pseudopanel Data in Travel Demand Analysis
• Future Mobility Survey: Experience in Developing a Smartphone-Based Travel Survey in Singapore
• Longitudinal Global Positioning System Travel Data and Breach of Privacy via Enhanced Spatial and Demographic Analysis
• Noncoverage Errors in Travel Surveys Due to Mobile Phone–Only Households
• On New Measures for Detection of Data Quality Risks in Mobility Panel Surveys
• Open Versus Closed: Effects of Question Form on Transit Rider Expressions of Policy Preferences in Arequipa, Peru
• Quantifying Key Errors in Household Travel Surveys: Comparison of Random-Digit-Dial Survey and Address-Based Survey
• Risk-Based Corridor Asset Management: Applying Multiattribute Utility Theory to Manage Multiple Assets
• Route Choice Characteristics for Truckers
• Stochastic Imputation of Missing Physical Commodity Trade Information Using Monetary Trade Data
• Strategic Total Highway Asset Management Integration