Reference Model of Desired Yaw Angle for Automated Lane Changing Behavior of Vehicle

In this paper,it studies the problem of trajectory planning and tracking for lane changing behavior of vehicle in automatic highway systems. Based on the model of yaw angle acceleration with positive and negative trapezoid constraint,by analyzing the variation laws of yaw motion of vehicle during a lane changing maneuver,the reference model of desired yaw angle and yaw rate for lane changing is generated. According to the yaw angle model,the vertical and horizontal coordinates of trajectory for vehicle lane change are calculated. Assuming that the road curvature is a constant,the difference and associations between two scenarios are analyzed,the lane changing maneuvers occurred on curve road and straight road,respectively. On this basis,it deduces the calculation method of desired yaw angle for lane changing on circular road. Simulation result shows that,it is different from traditional lateral acceleration planning method with the trapezoid constraint,by applying the trapezoidal yaw acceleration reference model proposed in this paper, the resulting expected yaw angular acceleration is continuous,and the step tracking for steering angle is not needed to implement. Due to the desired yaw model is direct designed based on the variation laws of raw movement of vehicle during a lane changing maneuver, rather than indirectly calculated from the trajectory model for lane changing, the calculation steps are simplified.     

基于反演法的智能车辆弯路换道轨迹跟踪控制

基于车辆的运动学模型,研究了具有非完整约束特性的智能车辆弯路换道的轨迹跟踪控制问题。结合弯曲车道的曲率半径,针对换道过程中车辆横向运动和纵向运动对换道轨迹的耦合作用,提出了一种适用于弯道的换道轨迹规划方法。根据换道轨迹,利用积分反演法,引入中间虚拟控制量,设计了轨迹跟踪控制算法,并用Lyapunov稳定性理论证明了控制系统的稳定性。仿真结果表明:该控制器可以保证车辆在弯路换道的轨迹跟踪误差一致有界收敛,且具有快速、准确跟踪和全局稳定的特性。     

Structured trajectory planning of collision-free lane change using the vehicle-driver integration data

In this paper, the structured trajectory planning of lane change in collision-free road environment is studied and validated using the vehicle-driver integration data, and a new trajectory planning model for lane change is proposed based on linear offset and sine function to balance driver comfort and vehicle dynamics. The trajectory curvature of the proposed model is continuous without mutation, and the zero-based curvature at the starting and end points during lane change assures the motion direction of end points in parallel with the lane line. The field experiment are designed to collect the vehicle-driver integration data, such as steering angle, brake pedal angel and accelerator pedal angel. The correction Correlation analysis of lane-changing maneuver and influencing variables is conducted to obtain the significant variables that can be used to calibrate and test the proposed model. The results demonstrate that vehicle velocity and Y-axis acceleration have significant effects on the lane-changing maneuver, so that the model recalibrated by the samples of different velocity ranges and Y-axis accelerations has better fitted performance compared with the model calibrated by the sample trajectory. In addition, the proposed model presents a decreasing tendency of the lane change trajectory fitted MAE with the increase of time span of calibrating samples at the starting stage.     

基于双五次多项式的智能汽车换道路径规划研究

快速准确地进行换道路径规划、有效跟踪期望路径以及换道过程中保持车辆的操纵稳定性,是保障智能汽车主动安全的核心技术.针对智能汽车主动换道过程中的路径规划问题,引入中转位置,提出基于双五次多项式的路径规划策略,以提高换道路径的平滑性,保证车辆换道安全性,满足换道实时性要求.对主动换道场景进行分析,确定换道初始及目标位置;基于车辆换道过程中的临界碰撞点,提出双五次多项式换道路径规划策略;建立联合仿真模型,针对不同道路状态进行主动换道仿真试验.结果表明：由于引入了中转点,利用双五次多项式规划方法得到的换道路径在临界碰撞状态前有更明显的侧向位移,能避开前方障碍车保证了换道安全性;换道中转位置处车辆最大侧向加速度不超过2 m/s²,保证了换道过程中车辆操纵稳定性;在干燥路面与湿润路面工况下,换道所需纵向安全距离减小20 m左右,保障了换道过程的纵向碰撞的安全性.研究结果可以为智能汽车主动换道路径规划提供理论及实践依据.     

侧向风干扰下的汽车主动前轮转向最优控制

侧向风对汽车行驶操纵稳定性有重要影响.通过分析侧向风干扰下车辆稳定性,提出基于主动前轮转向(active front wheel steering,AFS)的控制策略.AFS控制器采用线性二次型最优控制算法,以实现横摆角速度和质心侧偏角目标值跟踪.为了评价控制算法,基于MATLAB/Simulink和CarSim协同仿真环境建立整车动力学模型、单点预瞄驾驶员模型、控制器模型、道路和侧向风模型.仿真结果表明,AFS可有效提高车辆在侧向风干扰下的操纵稳定性,且控制算法对车速和路面附着系数具有良好的鲁棒性.     

高速无人驾驶车辆轨迹跟踪和稳定性控制

针对高速无人驾驶车辆运动控制过程中轨迹跟踪精度和稳定性难以同时保障的问题,提出综合前馈-反馈及自抗扰控制(ADRC)补偿相结合的横向控制算法. 通过车速和道路曲率信息计算前馈稳态前轮转向角,将质心侧偏角引入航向偏差,以车辆航向角偏差和侧向偏差作为参考量进行反馈控制,通过前馈-反馈控制提升瞬态轨迹跟踪性能. 设计自抗扰控制器,通过扩张状态观测器对未建模动态和内外界干扰进行估计,通过将后轮侧偏角控制在参考值附近来补偿前轮转角,提升无人驾驶车辆的转向稳定性和控制器的鲁棒性. 不同工况下的仿真结果表明,利用该方法可以保证高速无人驾驶车辆稳定地跟踪期望路径行驶,轨迹跟踪偏差较小,对车辆参数变化和外界干扰具有较强的鲁棒性.     

基于串级MPC和EPS的集成驾驶员转向车道线保持

针对电动助力转向( EPS)作为转向执行机构的车道线保持的控制系统设计及保留驾驶员对车辆操控问题,提出基于串级模型预测控制( MPC)和EPS集成驾驶员转向的车道线保持系统. 在车道线识别视觉系统空间,建立车道线保持状态空间模型,设计基于MPC的车道线保持控制器( LMPC) . 建立EPS状态空间模型,设计基于MPC的EPS车辆前轮转角控制器( EMPC) . LMPC与EMPC经逆转向机构模型组成串级控制结构. 分析驾驶员转向对车道线保持控制的影响,进而通过保留驾驶员对车辆控制来提高处理紧急事件的能力. 仿真结果表明:在不同车速和不同曲率道路下,该控制策略均能快速消除横向位置偏差和航向角偏差,保证车辆沿着车道线行驶,具有较好的适应性和鲁棒性. 驾驶员转向可以改善车道线保持和提高车辆主动安全性.     

Direct adaptive control for lane keeping in intelligent vehicle systems

In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent vehicle systems. Based on the dynamical model of vehicle, by applying Lyapunov function method, the control problem for lane keeping in the presence of parametric uncertainty is studied, the direct adaptive algorithm to compensate for parametric variations is proposed and the terminal sliding mode variable structure control laws are designed with look-ahead references systems. The stability of the system is investigated from the zero dynamics analysis. Simulation results show that convergence rates of the lateral displacement error, yaw angle error and slip angle are fast.     

自动化公路系统车队换道变结构控制

基于车辆纵横向动力学耦合模型,研究了自动化公路系统车队换道的纵横向耦合控制.假定车队中每个跟随车辆依靠车间通信接收引导车辆以及该车前面相邻车辆的位移、速度信息,利用车载传感器获得车辆横摆角速度信息.基于满足正反梯形约束条件的侧向加速度,计算车辆换道时的期望横摆角和横摆角速度.采用有限时间滑模趋近律,设计了车队换道纵横向耦合变结构跟踪控制规律,基于李雅普诺夫稳定性理论,对控制系统的稳定性进行分析.仿真结果显示,采用文中设计的控制规律,对于车队中每个跟随车辆,在实现车辆自动换道的同时,纵向上能够保持满意的车间距离.     

基于模糊-PID控制的对开路面汽车制动稳定性研究

提出了利用横摆力矩控制汽车在对开路面制动稳定性的方法.根据建立的动力学模型确立了相关的控制策略和控制模式,设计了参数自整定的模糊PID控制器,仿真与道路试验结果表明,利用汽车制动稳定性横摆力矩模糊-PID控制方法,能减少汽车在对开路面制动时的跑偏或激转等危险,且使汽车在制动偏驶后能快速恢复正确行驶车道,而将模糊-PID控制与模糊控制,PID控制得到的仿真结果进行对比也证明模糊-PID控制能更好的满足控制要求,从而验证了参数自整定模糊-PID控制方法对于提高汽车制动稳定性和行驶安全性的可行性.     

Map-based control method for vehicle stability enhancement

This work proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. A 2-DOF vehicle model and Pacejka's tire model are used to evaluate the proposed map-based control method. The properties of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with a low friction coefficient. However, map-based control determines a compensated yaw moment to maintain the vehicle within the stability region,so the typical responses of vehicle enable to converge rapidly. The simulation results with sine and step steering show that map-based control provides better the tracking responsibility and control performance than model-referenced control.     

Implementation of MPC-Based Trajectory Tracking Considering Different Fidelity Vehicle Models

In order to investigate how model fidelity in the formulation of model predictive control(MPC) algorithm affects the path tracking performance, a bicycle model and an 8 degrees of freedom(DOF) vehicle model, as well as a 14-DOF vehicle model were employed to implement the MPC-based path tracking controller considering the constraints of input limit and output admissibility by using a lower fidelity vehicle model to control a higher fidelity vehicle model. In the MPC controller, the nonlinear vehicle model was linearized and discretized for state prediction and vehicle heading angle, lateral position and longitudinal position were chosen as objectives in the cost function. The wheel step steering and sine wave steering responses between the developed vehicle models and the Carsim model were compared for validation before implementing the model predictive path tracking control. The simulation results of trajectory tracking considering an 8-shaped curved reference path were presented and compared when the prediction model and the plant were changed. The results show that the trajectory tracking errors are small and the tracking performances of the proposed controller considering different complexity vehicle models are good in the curved road environment. Additionally, the MPC-based controller formulated with a high-fidelity model performs better than that with a low-fidelity model in the trajectory tracking.     

Combined Control Allocation and Sliding Mode Control in the Dynamic Control of a Vehicle with Eight In-Wheel Motors

An eight wheel independently driving steering (8WIDBS) electric vehicle is studied in this paper. The vehicle is equipped with eight in-wheel motors and a steer-by-wire system. A hierarchically coordinated vehicle dynamic control (HCVDC) system, including a high-level vehicle motion controller, a control allocation, an inverse tire model and a lower-level slip/slip angle controller, is proposed for the over-actuated vehicle system. The high-level sliding mode vehicle motion controller is designed to produce desired total forces and yaw moment, distributed to longitudinal and lateral forces of each tire by an advanced control allocation method. And the slip controller is designed to use a sliding mode control method to follow the desired slip ratios by manipulating the corresponding in-wheel motor torques. Evaluation of the overall system is accomplished by sine maneuver simulation. Simulation results confirm that the proposed control system can coordinate among the redundant and constrained actuators to achieve the vehicle dynamic control task and improve the vehicle stability.     

车载移动执法中违规车辆智能检测研究

提出了一个面向高速道路交通车辆违规行为移动执法智能检测模型。系统模型分为车道线检测、车辆检测与跟踪、逆透视变换及几何量算、面向车道定位的地图精细匹配等4个子模块。该系统模型算法在实际高速公路环境中进行了车辆违规行为检测,以及车道线检测、车辆目标及跟踪等专项测试以表征其对车辆违规行为的检测能力。测试结果表明,该系统模型具备在一定的复杂交通环境中车辆违规行为辨识能力。相关专项测试表明,该模型可以快速及准确地检测记录违规车辆。     

提高车辆转向稳定性的车身主动侧倾控制研究

车辆高速转向时，车身向弯道外侧倾斜，严重时会导致侧翻事故.针对此问题，开展了提高车辆转向稳定性的车身主动侧倾控制研究.首先建立了考虑横摆和侧倾运动的六自由度车辆动力学模型；然后确定了车辆在转向运动时的期望侧倾角，并以此为控制目标设计主动侧倾控制器，使车身实际侧倾角逼近期望侧倾角.在不同行驶工况下，仿真研究了车身侧倾角、乘员感知加速度和横向载荷转移率，并考察了实现主动侧倾控制所需的主动悬架功耗和由主动侧倾引起的悬架动挠度变化.研究结果表明：主动侧倾控制能实现车辆转向时实际侧倾角迅速逼近期望侧倾角，且在复杂行驶工况下依然能使车辆具有良好的行驶稳定性；主动侧倾控制减小了悬架的动挠度峰值，使乘员感知侧向加速度和横向载荷转移率都能快速接近零值，且实现主动侧倾的主动悬架功耗较小，保证了车辆的经济性能.     

基于流量耦合分析的先出后入型快速路进出口方案设计

为确定先出后入型快速路进出口设计方案,考虑不同车流密度对通行能力计算模型的影响,计算不同的进出口车流条件下,快速路主路最外侧车道通行能力,通过对其分析比较以获取最佳快速路进出口设计方案,解决了目前的设计方案缺乏与流量耦合分析的问题。计算结果表明:当Q出<509pcu/h且Q入<509pcu/h时,采用出口道无减速车道-入口道无加速车道方案;当509pcu/h≤Q出<589pcu/h且509pcu/h≤Q入<589pcu/h时,采用出口道无减速车道-入口道设加速车道设计方案;当Q出≥589pcu/h且Q入≥589pcu/h时,采用出口道设减速车道-入口道设加速车道方案。     

半挂汽车转向稳定性反馈线性化控制

建立了半挂汽车非线性动力学模型,分析了车辆在低附着系数路面上高速转向行驶稳定性。采用遗传算法和相平面法估计了行驶速度为16.7～25m/s时车辆稳态前轮临界转角。基于非线性反馈线性化跟踪控制理论,以牵引车横摆角速度和铰接角为控制对象,设计了半挂汽车前轮主动转向和鞍座直接横摆力矩联合控制的前馈和反馈复合控制器。车辆高速阶跃转向和单移线工况仿真结果表明:联合控制器对于提高半挂汽车横向稳定性效果较好。     

Multi-constrained model predictive control for autonomous ground vehicle trajectory tracking

A multi-constrained model predictive control (MPC) algorithm for trajectory tracking of an autonomous ground vehicle is proposed and tested in this paper. First, to simplify the computation, an active steering linear error model is applied in the MPC controller. Then, a control increment constraint and a relaxing factor are taken into account in the objective function to ensure the smoothness of the trajectory, using a softening constraints technique. In addition, the controller can obtain optimal control sequences which satisfy both the actual kinematic constraints and the actuator constraints. The circular trajectory tracking performance of the proposed method is compared with that of another MPC controller. To verify the trajectory tracking capabilities of the designed controller at different desired speed, the simulation experiments are carried out at the speed of 3m/s, 5m/s and 10m/s. The results demonstrate the MPC controller has a good speed adaptability.     

基于主动横摆力矩优化分配的车辆底盘集成控制

基于二自由度车辆模型设计了车辆底盘集成控制器,开发了基于二次规划法的主动横摆力矩优化分配算法。针对阶跃转向和单移线转向行驶两种典型工况进行了仿真试验。结果表明,所设计的底盘集成控制器具有良好的控制效果,能够明显地改善车辆的操纵稳定性;开发的主动横摆力矩优化分配算法能够充分利用各个执行机构,使得在主动转向角和主动制动压力等输入都较小的情况下,能获得较好的车辆操纵稳定性。     

基于路面激励的动力总成受振特性分析及评价

为探求路面激励下车辆动力总成的受振特性,以动力总成质心振动加速度和相对振动位移为评价指标,建立了包含有6自由度动力总成模型的13自由度整车模型.以某等级道路轮廓和发动机自身振动为激励,分别进行了车速为60、45和30km/h的动力总成受振状态数值计算,分析了不同车速下动力总成的受振特点,并在振动加速度分析时提出了采用全程平均振动加速度的分析方法.研究结果表明：在同一路面轮廓下,车速越高则动力总成的质心振动加速度和相对振动位移越大,而各车速下动力总成偏转角度差别不大.