Introduction to Algorithms
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Learning dynamic adaptation strategies in agent-based traffic simulation experiments
MATES'11 Proceedings of the 9th German conference on Multiagent system technologies
Selfish road users --- case studies on rule breaking agents for traffic simulation
MATES'12 Proceedings of the 10th German conference on Multiagent System Technologies
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Simulations are widely used for modeling, analysis, planning, and optimisation of traffic flows and phenomena. For realistic traffic simulations within urban scenarios, the following tasks have to be solved: (1) modeling of the road structure; (2) specification of the behaviour on the road. In our days, very detailed road models for almost any major city exist in Geographic Information Systems (GIS). In the last two decades, the Nagel-Schreckenberg model (NaSch) has been established as de facto standard for car behaviour in freeway traffic due to its efficient and realistic simulations. Within urban scenarios, NaSch lacks of flexibility to integrate heterogeneous road users like cars and bicycles. The tasks mentioned before are addressed in this paper, i.e., we propose an approach for modeling and specification of urban mixed traffic simulations. As a first step (1), an extended graph as basis for traffic simulation has to be designed. For a concrete scenario, it will be automatically generated on basis of OpenStreetmap cartographical material. The specification of road user behaviour (2) has been influenced by the NaSch model. However, the model has been extended to cover the lack of NaSch in urban scenarios: A non cell-based approach is chosen for traffic movement. Furthermore, the routing of traffic users is based on either probability or A* based routing. In this paper, details on the modeling and specification are presented and experimental results are provided.