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Vehicular traffic congestion is a recurring and widespread societal phenomenon. Since drivers increasingly rely on routing services, we consider how to enhance such services to provide routes that mitigate congestion. Specifically, we propose the Congestion-mitigating Spatiotemporal Routing (CSR) problem that considers the congestion caused by vehicles following the routes provided. This problem is challenging because vehicles that follow recommended routes appear on different road segments at different times. We propose two solutions, Spatiotemporal Oblivious Routing (SOR) and Spatiotemporal Routing with History (SRH), which return routes based on the current and anticipated future traffic statuses, respectively, while offering theoretical guarantees. We also propose an update procedure for handling traffic dynamics. Extensive evaluations on real data provide insight into the properties of the solutions, indicating that SRH can reduce the number of vehicles on the most congested road segments by nearly 33 % and can process a query in less than 10 ms.
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Wang et al. (2024) studied this question.
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