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Next-Generation Intersection Control Powered by Autonomous and Connected Vehicle Technologies

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Information Technology and Intelligent Transportation Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 454))

Abstract

Urban intersections are one of the key bottlenecks that cause recurring congestions. Traditional signalized control is effective but capacity-restrained. Availability of autonomous and connected vehicle technologies provides the possibility to improve intersection capacity. Powered by autonomous and connected vehicle technologies, a next-generation intersection control strategy ACUTA was developed by employing a reservation-based centralized control strategy. ACUTA converts the conflicts between traffic movements into conflicts between individual vehicles, hence enhancing intersection capacity. Comparison between ACUTA and optimized signal control revealed that ACUTA increased the intersection capacity by 33 %, resulting substantially lower delays. Particularly, comparison of the v/c ratios indicated that ACUTA could process 163 more vehicles per hour per lane without being oversaturated when compared to optimized signal control. Sustainability-wise, as ACUTA minimizes vehicle stops at intersections, it reduces emission and energy consumption as well. Sustainability effects compared with signalized intersection control include: (1) ACUTA reduces CO and PM 2.5 emissions by about 5 % under low to moderate volume conditions and by about 3 % under high volume condition; and (2) energy consumption is reduced by about 4 % under low to moderate volume conditions and by about 12 % under high volume condition. All these enhancements validate the potential benefits of implementing the next-generation intersection control.

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Correspondence to Zhixia Li .

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© 2017 Springer International Publishing Switzerland

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Li, Z. (2017). Next-Generation Intersection Control Powered by Autonomous and Connected Vehicle Technologies. In: Balas, V., Jain, L., Zhao, X. (eds) Information Technology and Intelligent Transportation Systems. Advances in Intelligent Systems and Computing, vol 454. Springer, Cham. https://doi.org/10.1007/978-3-319-38789-5_12

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  • DOI: https://doi.org/10.1007/978-3-319-38789-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-38787-1

  • Online ISBN: 978-3-319-38789-5

  • eBook Packages: EngineeringEngineering (R0)

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