When security games hit traffic: Optimal traffic enforcement under one sided uncertainty

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Abstract

Efficient traffic enforcement is an essential, yet complex, component in preventing road accidents. In this paper, we present a novel model and an optimizing algorithm for mitigating some of the computational challenges of real-world traffic enforcement allocation in large road networks. Our approach allows for scalable, coupled and non-Markovian optimization of multiple police units and guarantees optimality. In an extensive empirical evaluation we show that our approach favorably compares to several baseline solutions achieving a significant speed-up, using both synthetic and real-world road networks.

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APA

Rosenfeld, A., & Kraus, S. (2017). When security games hit traffic: Optimal traffic enforcement under one sided uncertainty. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 0, pp. 3814–3822). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2017/533

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