Abstract
We present an approach for integrated decision making of vehicle agents in urban traffic systems. The planning process for a vehicle agent is broken down into two stages: strategic planning for selection of the optimal route and tactical planning for passing the current street in the most optimal manner. Vehicle routing is considered as a stochastic shortest path problem with imperfect knowledge about network conditions. Tactical planning is considered as a problem of collaborative learning with neighbor vehicles.We present planning algorithms for both stages and demonstrate interconnections between them; as well, an example illustrates how the proposed approach may reduce travel time of vehicle agents in urban traffic.
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© 2011 Springer-Verlag Berlin Heidelberg
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Fiosins, M., Fiosina, J., Müller, J.P., Görmer, J. (2011). Agent-Based Integrated Decision Making for Autonomous Vehicles in Urban Traffic. In: Demazeau, Y., Pěchoucěk, M., Corchado, J.M., Pérez, J.B. (eds) Advances on Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19875-5_22
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DOI: https://doi.org/10.1007/978-3-642-19875-5_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19874-8
Online ISBN: 978-3-642-19875-5
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