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An adaptive traffic signal coordination optimization method based on vehicle-to-infrastructure communication

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Abstract

The increasing volume of traffic in cities has a significant effect on the road traffic congestions and the time it takes for road users to reach their destinations as well. Adaptive signal control system has shown powerful ability to effectively alleviate urban traffic congestions to achieve desirable objectives (e.g., minimization of delay). The real-time adaptive traffic signal control system can obtain traffic density information by taking advantage of vehicle-to-infrastructure (V2I) communication system to prepare efficient measurement statistics for traffic controllers. In this paper, we present a novel multi-agent based control method for an integrated network of adaptive traffic signal controllers under V2I communication environment which is characterized by the following features: flow model free, area coordinated, co-learning and suitable for parallel processing. Our method has been tested on a large-scale network covering 23 km\(^{2}\) with 22 intersections in the downtown area of Xiaogan, China. The results show the significant reductions in the average travel time per vehicle, the average delay per vehicle and the average queue length, when compared to the data in the traditional fixed-time method and actuated method.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant No. 61375079).

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Authors and Affiliations

  1. Department of Automation, University of Science and Technology of China, Hefei, China

    Junping Xiang & Zonghai Chen

  2. Department of ITS, Lianyungang JARI Electronics Co., Ltd. of CSIC, Lianyungang, China

    Junping Xiang

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  1. Junping Xiang
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  2. Zonghai Chen
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Correspondence to Junping Xiang.

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Xiang, J., Chen, Z. An adaptive traffic signal coordination optimization method based on vehicle-to-infrastructure communication. Cluster Comput 19, 1503–1514 (2016). https://doi.org/10.1007/s10586-016-0620-7

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  • DOI: https://doi.org/10.1007/s10586-016-0620-7

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