基于弯道行驶的车辆自适应巡航控制
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摘要
自适应巡航控制系统(ACC)能够有效的减轻驾驶员疲劳强度并提高车辆行驶安全性。但是在弯道中，已有ACC系统采用的雷达目标提取算法无法实现对目标车辆的准确识别与跟踪；同时在弯道高速跟车过程中，ACC车辆还可能发生横向失稳的危险，而在原车直接横摆力矩控制(DYC)系统介入的过程中，ACC与其在某些工况下可能存在相互制约。针对上述问题，本文提出了弯道自适应巡航控制系统分层式多目标协调控制系统结构，并研究了该系统涉及的主要关键技术。
为了提高ACC系统在弯道工况下的环境感知能力，首先在不额外增加传感器的前提下对仅利用车载雷达的弯道目标车辆识别与跟踪算法进行研究，基于自车与前车相对速度及方位角的关系对前车换道和进出弯道的工况进行识别，同时基于前车相对自车的横向距离的估计值和实际值的一致性程度对弯道中本车道前车和邻车道前车进行区分。
为在弯道中保证ACC车辆横向稳定的前提下最大化其纵向跟车能力，利用滚动时域预测控制理论，提出一种基于DYC的弯道ACC纵向跟踪性和横向稳定性的协调控制方法，重点研究该协调系统控制器设计过程中所涉及的关键技术，包括弯道ACC系统控制对象即车辆的纵向动力学和横向动力学以及广义纵向车间动力学的集成建模，体现纵向跟踪性和横向稳定性的性能指标设计，以及滚动时域预测控制算法对模型不确定性的弱鲁棒性和在线计算高复杂度这两类实车实用化问题的求解。
然后，为实现上述协调控制器输出的期望加速度和期望附加横摆力矩这两个控制指令，对ACC系统与DYC系统的执行器结构共用技术进行研究，对弯道ACC系统的伺服控制器结构进行改进，以减少或消除ACC与DYC在结构共用过程中存在的矛盾。
为了验证本文系统的有效性，在三类弯道前车特定工况及道路附着条件下进行了驾驶员在环测试。试验结果表明，本文设计的弯道ACC系统可有效对弯道中的目标车辆进行准确识别与跟踪，可提高车辆在弯道自动跟车过程中的横向稳定性，同时减小DYC施加的附加制动力对纵向跟车性能的影响，并提高车辆在极限工况下的弯道跟车能力。
Adaptive Cruise Control (ACC) system has been believed to reduce driver’sworkload and improve driving safety effectively. However, existing ACC targetdetermination methods by radar cannot detect preceding vehicles properly on a curvedroad. And when ACC vehicle is running at a high speed to keep car-following on acurved road, it will even lose its lateral stability. A Direct Yaw-moment Control (DYC)system is always adopted to improve vehicle lateral stability. However, ACC and DYCare reversely interactive with each other in some driving situations. To address thoseissues, this thesis proposes a Curving ACC system that is coordinated with DYC andinvestigates its key technologies.
To improve the environment perception of ACC, a new algorithm for radar-basedtarget vehicle identification and tracking on curved roads for ACC applications isstudied firstly. The identification between target curve-entry/exit and lane-change isaehieved based on the different relationship between relative velocity and azimuth angle.And the distinction of the host-lane preceding vehicle from the adjacent-lane one whiledriving through a curve is realized based on the deviation of the measured lateraldistance from a theoretical value.
Then, to maximize longitudinal car-following capability while ensuring the lateralstability on curved road, a DYC based Curving ACC coordination controller is designedunder the framework of Receding Horizon Control theory, focusing on the generictechnologies study including predictive model building based on integrated vehiclelongitudinal/lateral dynamics and generalized inter-vehicle dynamics, performanceindex design considering the contradictions between vehicle longitudinal car-followingand lateral stability, and the derivation of practical problems as poor robustness to themodel uncertainties and high on-line computing complexity for receding optimizationalgorithm application on vehicles.
Moreover, to execute the control output of abovementioned coordination controlleras desired longitudinal acceleration and desired yaw moment, the technology for sharingthe same actuator structure between ACC and DYC is studied and the servo controllerof Curving ACC is modified so as to reduce or eliminate the unexpected behavior ofshared actuators.
To verify the validity of the Curving ACC system，a series of driver-in-the-looptests are carried out under three specified speed profiles of preceding vehicle andadhesion conditions on curved road and the test results confirm the followings. Thetarget vehicle around a curve can be properly identified and tracked by the proposedradar-based curving target vehicle identification and tracking method. The CurvingACC system can not only improve the lateral stability and weaken the impact of DYCextra brake on ACC longitudinal car-following performance, but also enhance thecar-following capability in limit conditions on curved road.
为了提高ACC系统在弯道工况下的环境感知能力，首先在不额外增加传感器的前提下对仅利用车载雷达的弯道目标车辆识别与跟踪算法进行研究，基于自车与前车相对速度及方位角的关系对前车换道和进出弯道的工况进行识别，同时基于前车相对自车的横向距离的估计值和实际值的一致性程度对弯道中本车道前车和邻车道前车进行区分。
为在弯道中保证ACC车辆横向稳定的前提下最大化其纵向跟车能力，利用滚动时域预测控制理论，提出一种基于DYC的弯道ACC纵向跟踪性和横向稳定性的协调控制方法，重点研究该协调系统控制器设计过程中所涉及的关键技术，包括弯道ACC系统控制对象即车辆的纵向动力学和横向动力学以及广义纵向车间动力学的集成建模，体现纵向跟踪性和横向稳定性的性能指标设计，以及滚动时域预测控制算法对模型不确定性的弱鲁棒性和在线计算高复杂度这两类实车实用化问题的求解。
然后，为实现上述协调控制器输出的期望加速度和期望附加横摆力矩这两个控制指令，对ACC系统与DYC系统的执行器结构共用技术进行研究，对弯道ACC系统的伺服控制器结构进行改进，以减少或消除ACC与DYC在结构共用过程中存在的矛盾。
为了验证本文系统的有效性，在三类弯道前车特定工况及道路附着条件下进行了驾驶员在环测试。试验结果表明，本文设计的弯道ACC系统可有效对弯道中的目标车辆进行准确识别与跟踪，可提高车辆在弯道自动跟车过程中的横向稳定性，同时减小DYC施加的附加制动力对纵向跟车性能的影响，并提高车辆在极限工况下的弯道跟车能力。
Adaptive Cruise Control (ACC) system has been believed to reduce driver’sworkload and improve driving safety effectively. However, existing ACC targetdetermination methods by radar cannot detect preceding vehicles properly on a curvedroad. And when ACC vehicle is running at a high speed to keep car-following on acurved road, it will even lose its lateral stability. A Direct Yaw-moment Control (DYC)system is always adopted to improve vehicle lateral stability. However, ACC and DYCare reversely interactive with each other in some driving situations. To address thoseissues, this thesis proposes a Curving ACC system that is coordinated with DYC andinvestigates its key technologies.
To improve the environment perception of ACC, a new algorithm for radar-basedtarget vehicle identification and tracking on curved roads for ACC applications isstudied firstly. The identification between target curve-entry/exit and lane-change isaehieved based on the different relationship between relative velocity and azimuth angle.And the distinction of the host-lane preceding vehicle from the adjacent-lane one whiledriving through a curve is realized based on the deviation of the measured lateraldistance from a theoretical value.
Then, to maximize longitudinal car-following capability while ensuring the lateralstability on curved road, a DYC based Curving ACC coordination controller is designedunder the framework of Receding Horizon Control theory, focusing on the generictechnologies study including predictive model building based on integrated vehiclelongitudinal/lateral dynamics and generalized inter-vehicle dynamics, performanceindex design considering the contradictions between vehicle longitudinal car-followingand lateral stability, and the derivation of practical problems as poor robustness to themodel uncertainties and high on-line computing complexity for receding optimizationalgorithm application on vehicles.
Moreover, to execute the control output of abovementioned coordination controlleras desired longitudinal acceleration and desired yaw moment, the technology for sharingthe same actuator structure between ACC and DYC is studied and the servo controllerof Curving ACC is modified so as to reduce or eliminate the unexpected behavior ofshared actuators.
To verify the validity of the Curving ACC system，a series of driver-in-the-looptests are carried out under three specified speed profiles of preceding vehicle andadhesion conditions on curved road and the test results confirm the followings. Thetarget vehicle around a curve can be properly identified and tracked by the proposedradar-based curving target vehicle identification and tracking method. The CurvingACC system can not only improve the lateral stability and weaken the impact of DYCextra brake on ACC longitudinal car-following performance, but also enhance thecar-following capability in limit conditions on curved road.
引文
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