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In order to make roadways safer for bicycles and pedestrians via infrastructure changes or in-vehicle technology warning systems for drivers, it is important to understand how drivers respond to such countermeasures, as well as to pedestrian and bicyclist behaviors.

The primary objective of this project is gain a better understanding of driver response to pedestrian and bicyclist behaviors through the convergence of epidemiological, observational, naturalistic, data to create simulated scenarios to test driver performance. The project will specifically focus on the impact of different infrastructure (e.g., bicycle lanes, crosswalks, refuge islands, etc.) and in-vehicle warning systems on driver response to bicyclists and pedestrians in typical settings and during safety-critical events (e.g., pedestrian distraction). Surveillance and naturalistic bicycle and pedestrian video data will be coded and considered, along with epidemiologic data, to identify patterns. From this analysis, the common variables will be extracted and used to develop several scenarios to examine driver response to bicyclists and pedestrians.