Fatally injured vulnerable road users, especially pedestrians who collided with motorised vehicles, account for 31% of all recorded fatalities in urban traffic in the EU. Autonomous vehicles will improve this situation in the future, reducing the impact of the human factor in critical traffic situations. The development of autonomous driving functions requires simulation environments to train certain behaviours. Consequently, these simulations need well represented vulnerable road users. In this paper, an approach for accurate prediction of pedestrian behaviour at street crossings is presented. The suggested solution involves an agent-based model working with A* pathfinding and risk-based areas, validated by a drone dataset on German road crossings.
Simulation of Pedestrian Behaviour in Traffic Situations Using Risk-Based A* Pathfinding
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 23 , 1 ; 441-449
2025-04-01
9 pages
Article (Journal)
Electronic Resource
English
Vulnerable road users , Agent-based simulations , Social force , Pathfinding , Risk aversion Information and Computing Sciences , Artificial Intelligence and Image Processing , Engineering , Civil Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , User Interfaces and Human Computer Interaction
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