基于多虚拟领航者的智能车编队控制研究
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南京林业大学 汽车与交通工程学院

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国家自然科学(61803206)


Research on Platooning control of Intelligent Vehicle based on Virtual Leaders
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College of Automobile and Traffic Engineering,Nanjing Forestry University

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    摘要:

    针对智能车队(SP)在通过无信号灯交叉口时稳定性差、通行效率低等难题,提出了一种基于多虚拟领航者(VL)的智能车编队控制方法。首先,以SP为研究对象,对传统人工势能函数(APF)进行改进,利用非线性函数关系描述智能车队系统内车-车之间的作用力。其次,基于虚拟领航思想,设计了基于多VL的SP成形改进人工势能函数蜂拥控制算法(IAPFFCA-VLs),并通过Lyapunov稳定性方法以及LaSalle不变性原理证明算法的稳定性。最后,利用Matlab进行SP成形控制仿真并与融合IAPF的蜂拥控制算法(FCA-IAPF)进行对比。实验结果表明,FCA-IAPF可以实现车-车间距控制与避碰,但是随着车辆数量的增多,会存在局部最优“分块”问题且不能形成规则编队。相较FCA-IAPF,IAPFFCA-VLs算法总体性能均得到了优化,可实现不同初始状态、不同数量而目的地相同的车辆保持合理间距、避碰的同时速度渐进达成一致,所有智能车与各自VL之间的位置距离误差终值小于0.1m、纵向速度误差终值小于1m/s、横向速度误差终值趋于0.001m/s,可以安全,迅速,稳定的约束为规则编队后驶出无信号灯交叉口,对提高无信号灯交叉SP行驶稳定性以及交通效率具有重要意义。

    Abstract:

    Aiming at the difficulties such as poor formation stability and low passage efficiency of smart platooning (SP) when passing through unsignalized intersections, an intelligent vehicle platooning control method based on Virtual Leaders (VLs) has been proposed. Firstly, taking the SP as the research object, improving the traditional artificial potential function (IAPF),using nonlinear functional relationships to describe the vehicle-vehicle forces within the SP system. Secondly, based on the idea of virtual navigation, an improved artificial potential function flocking control algorithm based on virtual leaders (IAPFFCA-VLs) for SP forming has been designed, and the stability of the algorithm has been proved by Lyapunov stability method and LaSalle invariance principle. Finally, using Matlab to simulate the SP forming control and compared with the flocking control algorithm incorporating IAPF (FCA-IAPF). The simulation results show that the FCA-IAPF can realize vehicle-vehicle distance control and collision avoidance, but with the increase of the number of intelligent vehicles, there is the problem of local optimal ‘chunking’ and can not form a regular SP. Compared to FCA-IAPF, the overall performance of the IAPFFCA-VLs algorithm are optimized, which can realize different initial states, different numbers of vehicles with the same destination to maintain reasonable spacing, avoiding collision while speed gradual to reach consistency, the positional distance deviation end-value between all intelligent vehicles and their respective VL is less than 0.1m, the longitudinal velocity deviation end-value is less than 1m/s, and the transverse velocity deviation end-value tends to be 0.001m/s, safe, rapid and stable constrained as a regular SP and drive out of the unsignalized intersection, which is important to improve the unsignalized intersection SP driving stability as well as traffic efficiency.

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肖广兵,邢启明,孙宁.基于多虚拟领航者的智能车编队控制研究[J].南京信息工程大学学报,,():

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  • 收稿日期:2024-05-22
  • 最后修改日期:2024-08-24
  • 录用日期:2024-08-24
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