Abstract
The vehicle-pedestrian encounter at midblock crosswalks in urban centers is inevitable but the challenge to urban transportation planners is in achieving a balance between traffic flow efficiency and pedestrian safety. Vehicles are expected to yield to pedestrians who have a right of way at the midblock unsignalized crosswalks but, failure to yield causes conflicts that at times are fatal. This study investigated the effect of macroscopic factors on the vehicle yielding. Six environmental factors are considered: temporal gap size, number of traffic lanes, number of waiting pedestrians, position of pedestrian (whether on street kerb or median), traffic flow direction and presence (or absence) of monitoring ePolice. Video Data on six observed variables that influenced vehicle yielding was collected from 13 uncontrolled crosswalk locations in Shanghai city in the Peoples Republic of China. A Logit model with a 95.9% accuracy was developed to describe the vehicle yielding behavior. The results showed that gap size and number of traffic lanes had the highest influence on driver yielding decision and that drivers were more likely to yield if ePolice was present. The sensitivity analysis was conducted and appropriate recommendations on improving the pedestrians crossing safety were proposed accordingly.
Highlights
Interaction between pedestrians and motor vehicles have continued to face increased conflicts over the years in many urban centers worldwide [1,2,3,4,5,6]
Sensitivity analysis was done to test the effects of the predictor variables on the outcome variable
Sensitivity Analysis is used in statistical modeling to analyze how different values of a set of predictor variables affect an outcome variable under specific varying conditions
Summary
Interaction between pedestrians and motor vehicles have continued to face increased conflicts over the years in many urban centers worldwide [1,2,3,4,5,6]. These conflicts happen when pedestrians cross a road segment, sometimes in a straight line, diagonally or zig-zag (rolling gap) and in both directions at formally designated sites (controlled or uncontrolled crosswalk) or at any site deemed convenient to the pedestrian [7]. A statistical analysis was performed on the data to establish the probability of driver yielding to pedestrians and correlations between the variables. Logit model was used to describe the probability of a driver yielding considering the variables in the study. Maximum likelihood evaluation was suitable for our study as it has no restrictions on the independent variables [45]
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