摘要: |
There is a national effort to reduce pedestrian deaths. To achieve this goal, a better understanding of pedestrian travel behavior and interactions with vehicles is needed. Using video surveillance of locations in Baltimore, Maryland, and Washington, D.C., this study compares pedestrian-related travel behavior in the two neighboring cities. A computer vision pipeline approach will be used to identify pedestrians and vehicles from video surveillance footage in order to extract key metrics such as walking speed, gap acceptance, and type of unsafe maneuvers, to characterize pedestrian crossing behavior and associated traffic patterns. Statistical analyses of these metrics will determine which factors – such as land use, infrastructure, and socio-demographic characteristics – contribute to pedestrian travel behavior decisions and safety. |