Abstract
This paper proposes a distributed self-learning algorithm based on the regret matching process in games for a dynamic route guidance. We incorporate a user’s past routing experiences and en-route traffic information into their optimal route guidance learning. The numerical study illustrates that the proposed self-guidance method can effectively reduce the travel times and delays of guided users in congested situation.
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Ma, TY. (2014). Distributed Regret Matching Algorithm for a Dynamic Route Guidance. In: Jezic, G., Kusek, M., Lovrek, I., J. Howlett, R., Jain, L. (eds) Agent and Multi-Agent Systems: Technologies and Applications. Advances in Intelligent Systems and Computing, vol 296. Springer, Cham. https://doi.org/10.1007/978-3-319-07650-8_12
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DOI: https://doi.org/10.1007/978-3-319-07650-8_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07649-2
Online ISBN: 978-3-319-07650-8
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