当前位置: X-MOL 学术IET Intell. Transp. Syst. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Gain-scheduling control of dynamic lateral lane change for automated and connected vehicles based on the multipoint preview
IET Intelligent Transport Systems ( IF 2.7 ) Pub Date : 2020-09-17 , DOI: 10.1049/iet-its.2020.0050
Zhigen Nie 1, 2 , Zhongliang Li 2 , Wanqiong Wang 1 , Weiqiang Zhao 3 , Yufeng Lian 4 , Rachid Outbib 2
Affiliation  

Dynamic lateral lane change (DLLC) control of automated and connected vehicles (ACVs) is challenging because of the time-varying and complex properties of the traffic environment. This study proposes a DLLC control strategy combining dynamic trajectory planning and tracking. According to the real-time longitudinal accelerations and velocities of multiple surrounding vehicles, as well as the real-time states of the ACVs, the safe trajectory reference of DLLC is obtained by solving a case-dependent constrained optimisation problem. The lane changing efficiency, vehicle stability and passenger comfort are considered jointly in the trajectory planning. Then, the dynamic trajectory reference is tracked through a gain-scheduling control algorithm combining previewed trajectory feed-forward and ACVs states feedback. Gain-scheduling control algorithm based on a linear time-varying form is utilised to achieve the precise control of the different velocities and improve the real-time ability of the algorithm. The proposed strategy is tested through software and hardware-in-loop experiments, and in different test scenarios. The results of simulations and experiments show that the proposed control strategy can achieve a satisfactory performance of DLLC. The lane changing efficiency, safety, passenger comfort and vehicle stability are verified in complex traffic environments.

中文翻译:

基于多点预览的自动和联网车辆动态横向车道变更的增益调度控制

由于交通环境的时变和复杂特性,对自动和联网车辆(ACV)进行动态横向车道变更(DLLC)控制非常具有挑战性。这项研究提出了结合动态轨迹规划和跟踪的DLLC控制策略。根据多辆周围车辆的实时纵向加速度和速度以及ACV的实时状态,通过解决基于案例的约束优化问题来获得DLLC的安全轨迹参考。轨迹规划中会同时考虑换道效率,车辆稳定性和乘客舒适度。然后,通过组合了预览的轨迹前馈和ACV状态反馈的增益调度控制算法来跟踪动态轨迹参考。利用基于线性时变形式的增益调度控制算法,实现了对不同速度的精确控制,提高了算法的实时性。通过软件和硬件在环实验以及在不同的测试场景中对所提出的策略进行了测试。仿真和实验结果表明,所提出的控制策略可以达到令人满意的DLLC性能。在复杂的交通环境中验证了变道效率,安全性,乘客舒适性和车辆稳定性。仿真和实验结果表明,所提出的控制策略可以达到令人满意的DLLC性能。在复杂的交通环境中验证了变道效率,安全性,乘客舒适性和车辆稳定性。仿真和实验结果表明,所提出的控制策略可以达到令人满意的DLLC性能。在复杂的交通环境中验证了变道效率,安全性,乘客舒适性和车辆稳定性。
更新日期:2020-09-18
down
wechat
bug