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Vehicle-pedestrian interaction (VPI) is one of the most challenging tasks forautomated driving systems. The design of driving strategies for such systemsusually starts with verifying VPI in simulation. This work proposed an improvedframework for the study of VPI in uncontrolled pedestrian crossing scenarios.The framework admits the mutual effect between the pedestrian and the vehicle.A multi-state social force based pedestrian motion model was designed todescribe the microscopic motion of the pedestrian crossing behavior. Thepedestrian model considers major interaction factors such as the accepted gapof the pedestrian's decision on when to start crossing, the desired speed ofthe pedestrian, and the effect of the vehicle on the pedestrian while thepedestrian is crossing the road. Vehicle driving strategies focus on thelongitudinal motion control, for which the feedback obstacle avoidance controland the model predictive control were tested and compared in the framework. Thesimulation results verified that the proposed framework can generate a varietyof VPI scenarios, consisting of either the pedestrian yielding to the vehicleor the vehicle yielding to the pedestrian. The framework can be easily extendedto apply different approaches to the VPI problems.

A Multi-State Social Force Based Framework for Vehicle-Pedestrian Interaction in Uncontrolled Pedestrian Crossing Scenarios