论文标题

遵循算法的汽车建模和分析,以改善连接和自动驾驶汽车的燃油经济性(CAVS)

Modelling and Analysis of Car Following Algorithms for Fuel Economy Improvement in Connected and Autonomous Vehicles (CAVs)

论文作者

Kavas-Torris, Ozgenur, Guvenc, Levent

论文摘要

地面车辆中的连通性允许车辆彼此共享重要的车辆数据,例如车辆加速。另一方面,使用摄像机,雷达和激光镜等传感器,可以检测到领导者和托管车辆之间的内距离,以及相对速度。合作自适应巡航控制(CACC)建立在地面车辆的连接和传感器信息的基础上,以随后自动汽车形成车队。 CACC还可以用来改善上述车队中车辆的燃油经济性和行动性能。在本文中,提出了3辆遵循骑士燃油经济性算法的汽车。自适应巡航控制(ACC)算法被设计为比较基准模型。设计了合作自适应巡航控制(CACC),它使用了通过V2V接收的铅车辆加速度。开发了一种生态合作自适应巡航控制(ECO-CACC)模型,该模型将不稳定的铅车辆加速度作为障碍。当铅车是不稳定的驾驶员时,设计用于决策的高水平(HL)控制器。运行了型号(MIL)和硬件式(HIL)模拟,以测试这些汽车,以供燃油经济性能进行算法。结果表明,HL控制器能够获得平稳的速度曲线,而当铅车辆不稳定时,使用CACC和ECO-CACC消耗的燃料少于其ACC对应物。

Connectivity in ground vehicles allows vehicles to share crucial vehicle data, such as vehicle acceleration, with each other. Using sensors such as cameras, radars and lidars, on the other hand, the intravehicular distance between a leader vehicle and a host vehicle can be detected, as well as the relative speed. Cooperative Adaptive Cruise Control (CACC) builds upon ground vehicle connectivity and sensor information to form convoys with automated car following. CACC can also be used to improve fuel economy and mobility performance of vehicles in the said convoy. In this paper, 3 car following algorithms for fuel economy of CAVs are presented. An Adaptive Cruise Control (ACC) algorithm was designed as the benchmark model for comparison. A Cooperative Adaptive Cruise Control (CACC) was designed, which uses lead vehicle acceleration received through V2V in car following. an Ecological Cooperative Adaptive Cruise Control (Eco-CACC) model was developed that takes the erratic lead vehicle acceleration as a disturbance to be attenuated. A High Level (HL) controller was designed for decision making when the lead vehicle was an erratic driver. Model-in-the-Loop (MIL) and Hardware-in-the-Loop (HIL) simulations were run to test these car following algorithms for fuel economy performance. The results show that the HL controller was able to attain a smooth speed profile that consumed less fuel through using CACC and Eco-CACC than its ACC counterpart when the lead vehicle was erratic.

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