Contextual Adjustment of the Institute of Transportation Engineers Trip Generation Rates for Small and Medium Urban Areas in Louisiana

Author:

Doulabi Saba1ORCID,Wilmot Chester1,Stopher Peter23ORCID,Antipova Angela4ORCID

Affiliation:

1. Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA

2. School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ

3. Institute of Transport and Logistics Studies, The University of Sydney Business School, Sydney, Australia

4. Department of Earth Sciences, University of Memphis, Memphis, TN

Abstract

The Institute of Transportation Engineers (ITE) Trip Generation Handbook has been in common use since the 1970s to estimate vehicle trips generated by more than 172 land use categories as a function of establishment size. However, observed trip rates display a huge error range across different land use categories and urban contexts. Although contextual adjustment factors can ameliorate the error in the ITE trip generation estimates considerably, local site-specific trip generation rates should be collected for this purpose. Given the huge time and monetary costs of data collection, adjusting the ITE trip generation rate is mainly done in large metropolitan areas such as Portland, OR, Baltimore, MD, and San Francisco, CA, while it is ignored by many jurisdictions in small to medium-sized metropolitan areas. Here, the ITE trip generation rates for strip mall land use in Louisiana are adjusted by considering the extent to which the built environment characteristics can improve the accuracy of estimated vehicle trip generation rates in smaller urban areas. Vehicle trip data were collected for two consecutive days at 40 strip malls across eight different urban areas of Louisiana to develop whole day and afternoon peak hour contextual adjustment factors for the given land use category across the study area. The results of this study show noticeable improvement for whole day analysis compared with the ITE method by producing a 42% reduction in root mean square error .

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

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