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Evaluation of the Energy Efficiency in a Mixed Traffic with Automated Vehicles and Human Controlled Vehicles

机译:自动驾驶汽车与人为控制汽车混合交通中的能效评估

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The energy efficiency of Connected and Automated Vehicles (CAVs) is significantly influenced by surrounding road users. This paper presents the evaluation of energy efficiency of CAVs in a mixed traffic interacted with human controlled vehicles. To simulate the interaction between the CAVs and the cut-in vehicles controlled by human drivers near the intersection, a lane changing model is proposed to emulate the politeness and patience characteristics of the human driver. The proposed lane changing model is then calibrated based on over 100,000 naturalistic lane changing events collected by the University of Michigan Safety Pilot Model Deployment Program. A case study on simulation of the cut-in scenario is carried out to demonstrate the human driver's lane changing sensitivity under different driving trajectories of a frontal CAV and the influence on the energy consumption of the CAV due to the cut-in vehicle is evaluated. The simulation results indicate that the fuel economy of the CAV can be substantially improved if its surrounding cut-in vehicles can be well handled.
机译:联网和无人驾驶汽车(CAV)的能源效率受周围道路使用者的影响很大。本文介绍了在与人为控制的车辆交互的混合交通中,CAV的能效评估。为了模拟CAV与交叉路口附近驾驶员控制的切入式车辆之间的交互作用,提出了一种车道变换模型,以模拟驾驶员的礼貌和耐心特性。然后根据密歇根大学安全飞行员模型部署计划收集的100,000多个自然主义的车道变换事件对建议的车道变换模型进行校准。通过对切入场景模拟的案例研究,证明了驾驶员在正面CAV的不同驾驶轨迹下的变道灵敏度,并评估了切入车辆对CAV能耗的影响。仿真结果表明,如果可以很好地处理其CAV周围的车辆,则可以大大改善CAV的燃油经济性。

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