Nonlinear ACC in Simulation and Measurement

In this paper an adaptive cruise control (ACC) of a convoy consisting of two passenger cars is designed and tested. For the ACC only on board sensors in the following vehicle are used, communication within the convoy or between the controlled vehicle and electronic systems on the roadside is not assumed. A laser scanner is applied for range measurements, derived from the complete vision data of the area in front of the car. Since the scanner provides the range only, a Kalman Filter is used to estimate the velocity and acceleration of the car. For controller design the concept of flat outputs in connection with the exact state linearization is applied. Moreover, the exact state linearization is combined with a sliding mode control. The control parameters are obtained by an optimization algorithm using optimal tracking formulation. The optimization also guarantees individual vehicle stability as well as string stability of the convoy. It is shown how the convoy is responding to disturbances resulting from initial errors or from velocity steps by the leading vehicle at lower speed in simulation and experiment.     

Automatic Cruise Control of a Mechatronically Steered Vehicle Convoy

In this paper a convoy of two vehicles is considered where the second one is mechatronically operated. The convoy model used for simulation and controller design is derived by the method of multibody systems. A nonlinear cruise controller based on the concept of flat outputs in connection with exact state linearization is derived. A nonlinear local observer is also implemented. It is shown that such a system responds properly to arbitrary maneuvers performed by the driver of the leading vehicle.     

Automatic Cruise Control of a Mechatronically Steered Vehicle Convoy

In this paper a convoy of two vehicles is considered where the second one is mechatronically operated. The convoy model used for simulation and controller design is derived by the method of multibody systems. A nonlinear cruise controller based on the concept of flat outputs in connection with exact state linearization is derived. A nonlinear local observer is also implemented. It is shown that such a system responds properly to arbitrary maneuvers performed by the driver of the leading vehicle.     

Robust design optimization of suspension system by using target cascading method

This study presents the robust design optimization process of suspension system for improving vehicle dynamic performance (ride comfort, handling stability). The proposed design method is so called target cascading method where the design target of the system is cascaded from a vehicle level to a suspension system level. To formalize the proposed method in the view of design process, the design problem structure of suspension system is defined as a (hierarchical) multilevel design optimization, and the design problem for each level is solved using the robust design optimization technique based on a meta-model. Then, In order to verify the proposed design concept, it designed suspension system. For the vehicle level, 44 random variables with 3% of coefficient of variance (COV) were selected and the proposed design process solved the problem by using only 88 exact analyses that included 49 analyses for the initial meta-model and 39 analyses for SAO. For the suspension level, 54 random variables with 10% of COV were selected and the optimal designs solved the problem by using only 168 exact analyses for the front suspension system. Furthermore, 73 random variables with 10% of COV were selected and optimal designs solved the problem by using only 252 exact analyses for the rear suspension system. In order to compare the vehicle dynamic performance between the optimal design model and the initial design model, the ride comfort and the handling stability was analyzed and found to be improved by 16% and by 37%, respectively. This result proves that the suggested design method of suspension system is effective and systematic.     

A curving ACC system with coordination control of longitudinal car-following and lateral stability

The paper presents a curving adaptive cruise control (ACC) system that is coordinated with a direct yaw-moment control (DYC) system and gives consideration to both longitudinal car-following capability and lateral stability on curved roads. A model including vehicle longitudinal and lateral dynamics is built first, which is as discrete as the predictive model of the system controller. Then, a cost function is determined to reflect the contradictions between vehicle longitudinal and lateral dynamics. Meanwhile, some I/O constraints are formulated with a driver permissible longitudinal car-following range and the road adhesion condition. After that, desired longitudinal acceleration and desired yaw moment are obtained by a linear matrix inequality based robust constrained state feedback method. Finally, driver-in-the-loop tests on a driving simulator are conducted and the results show that the developed control system provides significant benefits in weakening the impact of DYC on ACC longitudinal car-following capability while also improving lateral stability.     

Optimal Adaptive Cruise Control with Guaranteed String Stability

A two-level Adaptive Cruise Control (ACC) synthesis method is presented in this paper. At the upper level, desired vehicle acceleration is computed based on vehicle range and range rate measurement. At the lower (servo) level, an adaptive control algorithm is designed to ensure the vehicle follows the upper level acceleration command accurately. It is shown that the servo-level dynamics can be included in the overall design and string stability can be guaranteed. In other words, the proposed control design produces minimum negative impact on surrounding vehicles. The performance of the proposed ACC algorithm is examined by using a microscopic simulation program - ACCSIM created at the University of Michigan. The architecture and basic functions of ACCSIM are described in this paper. Simulation results under different ACC penetration rate and actuator/engine bandwidth are reported.     

Optimal Adaptive Cruise Control with Guaranteed String Stability

A two-level Adaptive Cruise Control (ACC) synthesis method is presented in this paper. At the upper level, desired vehicle acceleration is computed based on vehicle range and range rate measurement. At the lower (servo) level, an adaptive control algorithm is designed to ensure the vehicle follows the upper level acceleration command accurately. It is shown that the servo-level dynamics can be included in the overall design and string stability can be guaranteed. In other words, the proposed control design produces minimum negative impact on surrounding vehicles. The performance of the proposed ACC algorithm is examined by using a microscopic simulation program – ACCSIM created at the University of Michigan. The architecture and basic functions of ACCSIM are described in this paper. Simulation results under different ACC penetration rate and actuator/engine bandwidth are reported.     

基于目标速度的汽车ACC系统油门控制策略研究

ACC系统能够根据雷达等传感器检测到的前方车辆行驶信息,并自动控制本车的油门开度和制动强度,实现自适应巡航行驶,通过对车辆行驶纵向阻力特性的分析,针对目前广泛使用的基于目标加速度的油门开度控制策略受车辆装载质量影响较大的情况,利用功率平衡原理,提出了1种基于目标车速的油门开度控制策略,并利用PreScan软件对基于目标车速的油门开度控制策略进行了仿真实验,仿真结果表明了该控制策略有效的避免了整车装载质量变化对控制目标的影响。     

Predictive control of a vehicle trajectory using a coupled vector with vehicle velocity and sideslip angle

In this paper, a predictive algorithm for vehicle trajectory control using the vehicle velocity and sideslip angle is proposed. Since the driving state of a vehicle generates nonholonomic constraint equations, it is difficult to control the trajectory with a conventional control algorithm. Furthermore, control vectors such as vehicle velocity and sideslip angle are coupled together; hence, a separate control for each variable is not suitable. In this study, a coupled control vector that combines the velocity and sideslip angle is proposed for the predictive control of vehicle trajectory. Since the coupled control vector is derived from the status of the vehicle’s motion, it is easy to generate a feedback control vector for the predictive controller. The coupled vector cannot be directly used as input to the vehicle systems; therefore, the vehicle input vector should be calculated from the control vector using a nonlinear function. Since nonlinear functions are not inserted in the control loop, they are calculated by the controller. Therefore, this method does not require a linearization process in the control logic, which enhances the stability and accuracy of the predictive controller.     

Bond Graphs for Vehicle Dynamics

For the purposes of analyzing the stability and control properties of aircraft, automobiles, and ships, it is convenient to idealize the vehicle as a rigid body and to use a body-centered coordinate frame. A six-port bond graph is first developed which represents the nonlinear dynamics of a rigid body in a coordinate system rotating with the body. It is then shown how the graph simplifies if only lateral or longitudinal dynamics are studied. Finally, bond graphs for the type of stability studies in which the assumption of small perturbations permits linearization are shown for elementary models of automobiles and aircraft.     

汽车转向系统十字轴万向节传动优化设计

转向力是汽车操纵稳定性中一项重要的评价指标,其力矩波动直接影响驾驶感觉。文章对汽车转向轴的布置与力矩波动的关系进行了分析,并针对某车型转向系统的十字轴万向节结构进行优化设计。优化结果在matlab软件里仿真,得到较好的结果,波动力矩在允许的范围内。并得出最佳的中间轴相位角及轴系布置方案,对转向系统的优化设计有一定的参考价值,可作为实际车型开发中传动优化设计的技术依据。     

Using the lead vehicle as preview sensor in convoy vehicle active suspension control

Both ride quality and roadholding of actively suspended vehicles can be improved by sensing the road ahead of the vehicle and using this information in a preview controller. Previous applications have used look-ahead sensors mounted on the front bumper to measure terrain beneath. Such sensors are vulnerable, potentially confused by water, snow, or other soft obstacles and offer a fixed preview time. For convoy vehicle applications, this paper proposes using the overall response of the preceding vehicle(s) to generate preview controller information for follower vehicles. A robust observer is used to estimate the states of a quarter-car vehicle model, from which road profile is estimated and passed on to the follower vehicle(s) to generate a preview function. The preview-active suspension, implemented in discrete time using a shift register approach to improve simulation time, reduces sprung mass acceleration and dynamic tyre deflection peaks by more than 50% and 40%, respectively. Terrain can change from one vehicle to the next if a loose obstacle is dislodged, or if the vehicle paths are sufficiently different so that one vehicle misses a discrete road event. The resulting spurious preview information can give suspension performance worse than that of a passive or conventional active system. In this paper, each vehicle can effectively estimate the road profile based on its own state trajectory. By comparing its own road estimate with the preview information, preview errors can be detected and suspension control quickly switched from preview to conventional active control to preserve performance improvements compared to passive suspensions.     

Time-optimal control of the race car: a numerical method to emulate the ideal driver

A numerical method for the time-optimal control of the race car is presented. The method is then used to perform the role of the driver in numerical simulations of manoeuvres at the limit of race car performance. The method does not attempt to model the driver but rather replaces the driver with methods normally associated with numerical optimal control. The method simultaneously finds the optimal driven line and the driver control inputs (steer, throttle and brake) to drive this line in minimum time. In principle, the method is capable of operation with arbitrarily complex vehicle models as it requires only limited access to the vehicle model state vector. It also requires solution of the differential equation representing the vehicle model in only the forward time direction and is hence capable of simulating the full vehicle transient response.     

基于状态空间采样的高速公路智能网联车辆轨迹动态规划

为实现智能网联车辆在高速公路动态行车环境下的轨迹实时规划，提出一种基于状态空间采样的轨迹动态规划方法。首先，以安全性为原则选取主车当前行驶的理想车道。基于Frenet坐标与笛卡尔坐标的转换关系，建立车辆运动横、纵向解耦的独立积分系统。将高速公路常见的行驶状态分为车道保持与定速巡航、变道以及前车跟随3类，预测主车行驶车道并针对3类行驶状态分别设计轨迹终端的目标配置方法。然后，利用多项式函数生成连接初始配置和目标配置的多条待选轨迹。构建考虑轨迹偏离理想车道程度、始末速度变化、规划周期和轨迹舒适性的综合损失函数，结合速度、加速度、曲率检查来评价各条待选轨迹的成本并进行排序。最后，预测车辆的横、纵向运动轨迹并构建一种胶囊形的车辆虚拟安全边界，通过碰撞检测，确定主车的最优轨迹，设置动态规划触发条件及时更新最优轨迹并避免过度规划浪费资源。研究结果表明：提出的算法能满足高速公路场景的动态规划需求；通过对轨迹规划周期、虚拟安全边界、动态规划时间间隔等关键参数的分析与优化，主车的横摆角速度范围稳定在-0.1~0.15 (°)·s^-1，横向加速度范围稳定在-0.16~0.32 m·s^-2，跟踪参考轨迹的最大误差不超过0.022 m，提出的算法能规划出具有高安全性、稳定性和舒适性的轨迹。     

Bond Graphs for Vehicle Dynamics

SUMMARY

For the purposes of analyzing the stability and control properties of aircraft, automobiles, and ships, it is convenient to idealize the vehicle as a rigid body and to use a body-centered coordinate frame. A six-port bond graph is first developed which represents the nonlinear dynamics of a rigid body in a coordinate system rotating with the body. It is then shown how the graph simplifies if only lateral or longitudinal dynamics are studied. Finally, bond graphs for the type of stability studies in which the assumption of small perturbations permits linearization are shown for elementary models of automobiles and aircraft.     

智能车小车转向系统的建模与仿真分析

文章依据典型的线性二自由度汽车模型结合freescale智能小车的实际转向系统建立数学模型，推导出微分方程，采用比例微分控制（PD）策略，并结合系统模型运用MATLAB进行仿真。采用比例微分控制（PD）策略对小车的转向系统的信号延时进行改进，对稳定性等方面也进行改善，达到预期的优化目的。     

Model predictive control with constraints for a nonlinear adaptive cruise control vehicle model in transition manoeuvres

A vehicle following control law, based on the model predictive control method, to perform transition manoeuvres (TMs) for a nonlinear adaptive cruise control (ACC) vehicle is presented in this paper. The TM controller ultimately establishes a steady-state following distance behind a preceding vehicle to avoid collision, keeping account of acceleration limits, safe distance, and state constraints. The vehicle dynamics model is for continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. The ACC vehicle can execute the TM successfully and achieves a steady-state in the presence of complex dynamics within the constraint boundaries.     

FSC赛车空气套件CFD优化设计

在满足FSC赛车设计规则要求前提下,对空气套件进行了结构优化设计,重点完成了赛车尾翼的优化设计和分析。利用CFD技术对赛车车身模型进行了外流场分析,并通过在赛车尾部加装不同间隙和攻角的尾翼,进行车身外流场模拟对比分析,研究尾翼在改善赛车气动特性方面的影响规律,研究确定了空气动力学装置在不同比赛项目时的调教策略。通过对比分析赛车车辆周围气流的压力分布和速度分布规律,研究高速赛车的负升力效果,对于提高赛车的操纵稳定性和安全性具有非常重要的意义,对于指导赛车尾翼的正确安装、确定尾翼在不同比赛项目时的调教策略有一定的指导意义。     

自适应巡航及协同式巡航对交通流的影响分析

自适应巡航（ACC）和协同式自适应巡航（CACC）等自动驾驶技术正逐渐进入市场，未来一段时间内道路交通流将由人工驾驶车辆与不同等级、不同形式的自动驾驶车辆混合构成。为分析ACC和CACC对交通流的影响，利用实测交通数据NGSim建立人工驾驶车辆跟驰模型，并在综合已有ACC和CACC模型的基础上，提出基于安全间距的自动驾驶跟驰行为模型，进而得出不同ACC，CACC车辆渗透率下交通流的基本图模型。研究结果表明：自动驾驶可以提升交通容量；与ACC车辆比例r_a相比，CACC车辆比例r_c对交通容量的影响更为显著；当r_c>0.5时，饱和流量快速增加，当r_c=1时，饱和流量约为纯人工驾驶时的2倍。进一步，通过仿真考察车辆在车队中的跟驰响应和交通流在瓶颈处的运行情况。研究结果表明：自动驾驶改善了交通流的动态特性，对存在跟驰关系的连续车流来说，自动驾驶使得后车可以更加及时地响应前车的行为，车流会在更短的时间内进入稳态；在交通瓶颈处，自动驾驶降低了拥堵程度，提高了阻塞发生的临界流量。总体来看，自动驾驶对交通流静态和动态性能均有所提升，特别是在协同式自动驾驶场景下，车辆行为更加协调一致，交通流表现出良好的抗扰性，进一步验证了车路协同对自动驾驶的意义。     

基于多目标粒子群优化算法的某轻型商用车操纵稳定性优化研究

针对某轻型商用车稳态回转时侧倾度偏大的问题对其悬架进行优化改进。基于ADAMS/car搭建整车多体动力学模型,通过前悬架反向平行轮跳试验、后悬架理论计算验证了悬架仿真模型的准确性。进行整车稳态回转工况和转向盘中间位置转向工况仿真分析,结果表明,车身侧倾度偏高。为实现操纵稳定性优化分析的流程自动化,提出了基于modeFRONTIER的联合仿真方法。以悬架设计参数为优化变量,以汽车的侧倾度与横摆角速度响应滞后时间为优化目标,采用拉丁超立方试验设计方法拟合得到混合代理模型,并结合多目标粒子群优化算法对悬架系统进行多目标优化,获得了悬架系统优化方案。优化结果显示,在不影响平顺性的前提下,汽车车身侧倾度降低了13.93%,横摆角速度响应滞后时间降低了2.75%,整车操纵稳定性得到了提升。