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.
CITATION STYLE
Ma, T. Y. (2014). Distributed regret matching algorithm for a dynamic route guidance. In Advances in Intelligent Systems and Computing (Vol. 296, pp. 107–116). Springer Verlag. https://doi.org/10.1007/978-3-319-07650-8_12
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