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A Study on the Traffic Predictive Cruise Control Strategy With Downstream Traffic Information

机译：基于下游交通信息的交通预测巡航控制策略研究

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摘要

A vehicle traffic predictive cruise control (TPCC) system, responding to the change of downstream traffic situation, has been proposed to improve traffic operation and the fuel efficiency of vehicle based on the asymmetric traffic theory. The proposed predictive cruise control system consists of four parts: 1) deceleration-based safety surrogate measure (DSSM); 2) single-vehicle control algorithm; 3) multivehicle safety measurement (Co-DSSM); and 4) TPCC. The single-vehicle control algorithm basically decides the acceleration action based on estimated safety state between a subject vehicle and the immediate preceding vehicle, and the control strategy is determined by asymmetric driving behavior. Then, TPCC adjusts the amount of acceleration based on the Co-DSSM from multiple downstream vehicles, which contains the information on future traffic condition of the subject vehicle. A simulation using the real vehicle trajectories from the Next Generation Simulation (NGSIM) data validates the proposed TPCC system, and we compare the results with the real vehicles' car-following patterns. It is found that the proposed TPCC system can contribute to both the energy consumption and traffic flow operation by obtaining a higher level of traffic stability. Such results are due to the effects of suppressing the shockwave from downstream traffic and removing the unnecessary deceleration and acceleration actions.
机译：提出了一种基于下游交通状况变化的车辆交通预测巡航控制（TPCC）系统，以基于非对称交通理论来改善车辆的交通运营和燃油效率。拟议的预测巡航控制系统包括四个部分：1）基于减速的安全替代措施（DSSM）； 2）单车控制算法； 3）多车安全测量（Co-DSSM）；和4）TPCC。单车辆控制算法基本上基于目标车辆和紧前车辆之间的估计安全状态来决定加速动作，并且控制策略由非对称驾驶行为来确定。然后，TPCC根据来自多个下游车辆的Co-DSSM调整加速度，其中包含有关目标车辆未来交通状况的信息。使用来自下一代仿真（NGSIM）数据的真实车辆轨迹进行的仿真验证了所提出的TPCC系统，并且我们将结果与真实车辆的乘车模式进行了比较。发现所提出的TPCC系统可以通过获得更高水平的交通稳定性来对能量消耗和交通流运行做出贡献。这样的结果归因于抑制来自下游交通的冲击波并消除了不必要的减速和加速作用的效果。

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