Abstract
The development of Internet of vehicle (IOV) and autopilot technology indicates the coming of smart traffic and automatic unmanned era. The promotion of networking and intelligence not only provides a rich source for urban traffic data, but also provides an efficient and direct way to solve urban traffic problems. With the help of deep learning and reinforcement learning technology, we propose a model to mine the urban traffic rule from the travel history of urban travelers, and utilize it achieving better allocation of traffic resources by providing a traffic guidance service, finally realize the system optimal traffic travel.
This work was supported in part by the Natural Science Foundation of China under Grant 61876023 and Grant 61902035, and in part by the Natural Science Foundation of Beijing under Grant 4181002.
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Acknowledgement
This work was supported in part by the Natural Science Foundation of China under Grant 61876023 and Grant 61902035, and in part by the Natural Science Foundation of Beijing under Grant 4181002.
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Chen, K., Liu, Z., Li, J., Yuan, Q. (2020). A Road Traffic Guidance Service Based on Deep Reinforcement Learning. In: Hsu, CH., Kallel, S., Lan, KC., Zheng, Z. (eds) Internet of Vehicles. Technologies and Services Toward Smart Cities. IOV 2019. Lecture Notes in Computer Science(), vol 11894. Springer, Cham. https://doi.org/10.1007/978-3-030-38651-1_28
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DOI: https://doi.org/10.1007/978-3-030-38651-1_28
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