Download PDFOpen PDF in browserSituated and sequential planning and prediction of human driving behavior as decision making support system11 pages•Published: July 12, 2024AbstractThe realization of safe networked traffic is getting more and more important. The planning and prediction of possible driving behaviors and the detection of missing actions in advance contribute to avoid critical situations. A decision making system enables the support the human operator (driver) and to supervise the human-machine interaction by proposing possible actions predicted by the system, by warning him or her by detecting critical situations, and to take over the driving functionality if necessary.The contribution of the work is the development of a monitoring decision making system allowing the planning and prediction of possible driving behaviors, detection of missing actions, and to support the human operator to reach desired situations. A Situation Operator Modeling method is used as event-discrete approach to describe changes from the real world as well as driving behaviors as a graph-based model considering the changes in the environment. The behaviors of traffic-vehicles are calculated based on predicted trajectories using a Long Short-Term Memory (LSTM) Encoder Decoder algorithm. The approach is applied to an ’overtaking maneuver on a highway’. Decision options can be continually generated depending on the changes in the environment, can be suggested to the driver, and can support him or her to lead desired situations. Keyphrases: decision-making support system, Situated behavior planning and prediction, Situation-Operator-Modeling, Supervision of Human-Machine-interaction, Vehicle systems In: Kenneth Baclawski, Michael Kozak, Kirstie Bellman, Giuseppe D'Aniello, Alicia Ruvinsky and Candida Da Silva Ferreira Barreto (editors). Proceedings of Conference on Cognitive and Computational Aspects of Situation Management 2023, vol 102, pages 9--19
|
