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Signal control optimization for automated vehicles at isolated signalized intersections

机译:隔离信号交叉口的自动驾驶车辆信号控制优化

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摘要

Traffic signals at intersections are an integral component of the existing transportation system and can significantly contribute to vehicular delay along urban streets. The current emphasis on the development of automated (i.e., driverless and with the ability to communicate with the infrastructure) vehicles brings at the forefront several questions related to the functionality and optimization of signal control in order to take advantage of automated vehicle capabilities. The objective of this research is to develop a signal control algorithm that allows for vehicle paths and signal control to be jointly optimized based on advanced communication technology between approaching vehicles and signal controller. The algorithm assumes that vehicle trajectories can be fully optimized, i.e., vehicles will follow the optimized paths specified by the signal controller. An optimization algorithm was developed assuming a simple intersection with two single-lane through approaches. A rolling horizon scheme was developed to implement the algorithm and to continually process newly arriving vehicles. The algorithm was coded in MATLAB and results were compared against traditional actuated signal control for a variety of demand scenarios. It was concluded that the proposed signal control optimization algorithm could reduce the ATTD by 16.2-36.9% and increase throughput by 2.7-20.2%, depending on the demand scenario.
机译:交叉路口的交通信号是现有交通系统不可或缺的组成部分,可极大地助长沿城市街道的车辆延误。当前对自动(即无人驾驶并且具有与基础设施进行通信的能力)车辆的开发的重视在最前面提出了与信号控制的功能和优化有关的几个问题,以便利用自动车辆的能力。这项研究的目的是开发一种信号控制算法,该算法允许基于进近车辆与信号控制器之间的先进通信技术共同优化车辆路径和信号控制。该算法假定可以完全优化车辆的轨迹,即车辆将遵循信号控制器指定的优化路径。假设通过与两个单车道的简单交点来开发优化算法。开发了滚动视野方案以实施该算法并连续处理新到达的车辆。该算法在MATLAB中进行了编码,并将结果与​​各种需求场景下的传统驱动信号控制进行了比较。结论是,根据需求情况,所提出的信号控制优化算法可以使ATTD降低16.2-36.9%,并使吞吐量提高2.7-20.2%。

著录项

  • 来源
    《Transportation research》 |2014年第12期|1-18|共18页
  • 作者单位

    University of Florida, 365 Weil Hall, PO Box 116580, Gainesville, FL 32611, United States;

    University of Florida, 365 Weil Hall, PO Box 116580, Gainesville, FL 32611, United States;

    Department of CISE, University of Florida, Gainesville, FL 32611, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Automated vehicle; Signal control optimization;

    机译:自动驾驶汽车;信号控制优化;

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