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Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
An analysis of pedestrian safety at bus stops using FARS data
Allison Rewalt1, Candace Brakewood1, Christopher Cherry1
1Department of Civil and Environmental Engineering, University of Tennessee, 851 Neyland Drive, Knoxville, TN 37996, United States.
Introduction:
Bus stops must be safely accessible to transit passengers who begin and end their trips as pedestrians. Prior studies have analyzed bus stop safety using crash data, but many assumed that all crashes near bus stops were directly related to the stop itself, largely due to the lack of transit-related information in crash data. This research addresses this gap by analyzing fatal "transit bus stop-related" pedestrian crashes from the Fatality Analysis Reporting System (FARS) and comparing them to other nearby fatal pedestrian crashes.
Methodology:
A descriptive analysis, crosstabulation, binary logit models, and hierarchical clustering were used to compare fatal transit bus stop-related pedestrian crashes and other fatal pedestrian crashes within a quarter- and half-mile radius.
Results:
Most fatal crashes in both groups occurred midblock, on higher-speed roads, and on arterials, consistent with established pedestrian crash risk factors. The subsequent analysis focused on isolating risks specifically associated with bus stops. The binary logit models indicated that midblock locations, pedestrians stationary on the roadside, and bus-involved crashes significantly increased the odds of a crash being transit bus stop-related. Notably, midblock crashes had 4.7 to 5.2 times the odds of being transit bus stop-related. The clustering revealed three transit bus stop-related crash scenarios: (1) crossing to/from an intersection stop, (2) waiting on the roadside at a midblock stop, and (3) crossing to/from a midblock stop. Clustering the combined sample of fatal transit bus stop-related and nearby fatal crashes revealed a distinct cluster, predominantly composed of transit bus stop-related crashes characterized by pedestrians waiting on the roadside.
Conclusions:
Different stages of a transit passenger's journey represent distinct crash types, and midblock stops are especially high-risk.
Practical Applications:
Crossing improvements and speed reductions may benefit both transit passengers and nearby pedestrians. Evaluating conditions directly at the bus stop may further improve transit passenger safety.
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