Modeling Pedestrian Trip Generation in Urban Areas (original) (raw)

2006

Abstract

This study investigates factors that can be used to quantify peak hour daily pedestrian trips in urban areas in order to help estimate pedestrian trips. Various models are developed for morning peak, evening peak, evening off-peak, and combined daily peak hours depending on the type of the facilities near the high pedestrian activity locations. General linear regression modeling and other statistical methods are used to identify the significant factors. The best subset regression is used to model four different peak hour pedestrian volumes and the F-test is used to support the analysis. Various criteria are evaluated to select the best model. The model is validated and calibrated using data from the Las Vegas metropolitan area. The findings show that the daily peak hour pedestrian trips are a function of number of lanes, average annual household income and residential area proximate to the study location. Results show that the pedestrian trips are independent of the commercial area ...

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