Machine learning for social coordination of autonomous vehicles with human road users

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As part of the research activities in the Institute for Transport Studies (ITS) toward sustainable transportation systems and improving the safety of pedestrians and, the research will focus on understanding the social interaction of pedestrians and vulnerable human road users with automated vehicles (AVs) to improve the safety of urban traffic and the lower the rate of accidents due to false decision making and manoeuvre by the AVs. Using publicly available datasets and the University of Leeds driving simulator data, the research tries to understand pedestrians' behaviour in traffic scenes, enhance the accuracy of the existing machine vision-based models and contributes to the academic research gaps in the field; hence improving the performance and safety of automated driving functions. The student may also collaborate with other researchers in ITS with a background in psychology and human factor for a better understanding of vehicle/pedestrian interactions. All research activities in our human factors and safety research group at ITS Leeds aim at one common objective: maintaining resilient and safer transportation systems while reducing the number of traffic accidents, fatalities, and injuries.