Modeling Pedestrian and Bicyclist Crash Exposure with Location-Based Service Data

The rising popularity of non-motorized transportation has brought about safety risks. The inclusion of accurate traffic volume information is one of the key elements to produce robust outcomes when researching safety. The project investigates and enhances transportation safety for pedestrians and bicyclists, emphasizing the integration of Location-Based Services (LBS) data, particularly StreetLight data, to analyze traffic volume and associated risks. The calibration process demonstrates the significance of traffic volume as a key variable influencing prediction accuracy across pedestrian, bicyclist, and vehicle models. The crash analysis reveals a strong correlation between crash counts and traffic activity, with noteworthy findings emerging at the facility scale. The safety ranking analysis identifies higher and lower risk areas in the city. The spatial and temporal analysis at the street segment level highlights changes in traffic volumes before and during the COVID-19 period, along with distinct geographic patterns of activities at downtown and recreational locations. The project contributes to the knowledge and methodology surrounding transportation safety for non-motorized road users. By leveraging LBS data, the research provides comprehensive analyses of traffic patterns and safety considerations, aiming to create a safer environment for pedestrians and bicyclists