基于自适应采样时间MPC的自动紧急制动系统

针对传统AEB系统控制过程中缺乏对舒适性考虑以及控制精度较差等问题，提出了一种考虑多目标的模型预测控制（MPC）策略。首先，通过引入模糊规则计算场景工况的紧急系数，并基于此设计自适应采样时间MPC上层控制器，接着采用PID反馈控制与逆发动机模型设计下层控制器，最后通过PreScan与Simulink联合平台进行仿真试验，并进一步在实车试验平台上验证。结果表明，基于本文策略的AEB系统在两种典型场景、多种运行工况下均能避撞成功，加速度变化率始终位于舒适区间，最终车间距离为1.74～4.18 m，能确保车辆自动紧急制动过程中的舒适性与有效性。     

智能网联车辆队列紧急工况控制策略设计

目前针对紧急工况的智能网联车辆队列控制研究较为欠缺，为了解决高速公路车辆队列在紧急工况下安全、稳定控制问题，本文针对队列紧急制动、他车插入队列这两种紧急工况开展控制策略研究。首先，建立控制系统分层架构，由策略层和控制层组成。其中，控制层根据策略层的输出结果激活对应的车辆纵横向控制器；针对策略层，分别设计两种紧急工况的控制策略以及不同工况间的控制切换策略。最后，基于PreScan/Simulink搭建高速公路车辆队列控制联合仿真平台，设计包含多个紧急工况的复杂验证场景，完成五车队列在该场景下的仿真验证，并探讨了通信时延对控制性能的影响。仿真结果表明：该队列控制系统能保证队列在两种紧急工况下安全、稳定行驶，并可实现不同工况的切换控制。     

基于视觉传感器的ADAS纵向行驶工况识别方法研究

汽车先进驾驶辅助系统在应用时要根据不同的车辆行驶工况对车辆进行相应的控制,而准确的车辆行驶工况识别信号是合理的控制策略的基础.为了得到准确的车辆行驶工况识别信号,利用视觉传感器分别对车辆跟踪定位,以及车道线检测技术进行了研究.利用adaboost分类器检测出前方车辆;应用文中提出的基于坐标映射与定比分线并能够抵抗俯仰角干扰的测距方法进行车辆定位,验证结果显示该测距方法误差小于1m;再应用改进后的基于置信度判断与Kalman滤波技术的车道线跟踪检测方法进行车道线检测,并通过实车道路试验对此进行了验证,验证结果显示该车道线检测方法误差小于1°.提出1种基于PreScan的将所应用的车辆跟踪测距与车道线跟踪检测方法相结合的方法,用以实现汽车ADAS纵向行驶工况的识别,并通过PreScan仿真场景验证了该工况识别方法,结果表明该方法能够为ADAS提供准确的工况识别信号.      

重型车辆自适应巡航系统预测控制算法开发

自适应巡航(Adaptive Cruise Control,简称"ACC")系统是一种可以有效减轻驾驶员疲劳,提高行车安全性,改善道路通行效率,提高车辆燃油经济性的高级驾驶员辅助系统。在重型车辆领域,该方面研究较少,随着国内陆运交通及物流行业的飞速发展,ACC系统拥有广阔的应用前景。文章以陕汽SX1318高原运输车为目标车型,设计了基于模型预测控制(Model Predictive Control,简称"MPC")的ACC系统控制算法,依据目标车型的性能参数,以提高驾乘舒适性为主要目标,制定了相应的控制策略。以Simulink和车辆动力学仿真软件Truck Sim为平台,建立了目标车型整车纵向动力学联合仿真模型,用来研究在不同巡航工况下对前方目标车辆的跟随能力及本车的行驶舒适性。仿真和实车试验测试结果表明,文章所设计的ACC系统算法,在保持预期的安全距离情况下,能有效满足性能指标要求。     

汽车ACC跟随控制策略研究

提出了ACC车辆与前车之间的速度一位移关系以及分别以车距控制和相对车速控制为目标的2种LQR模型，并根据两车的速度一位移关系的不同实现2种模型之间的转换，以生成符合驾驶员操作行为的ACC车辆控制目标，建立了实现控制目标的车速控制模型。仿真计算表明控制策略满足乘坐舒适性和保持安全车距的要求。     

车辆自适应巡航控制系统的建模与分层控制

为改善车辆自适应巡航控制(ACC)系统的功能,本文中研究一种ACC系统建模和分层控制方法。首先建立考虑纵向、侧向和垂向耦合特性的14自由度整车模型,并根据电子节气门和制动器的实际物理特性建立能准确跟踪期望输入的执行器模型。接着建立包含驱动/制动切换逻辑、发动机逆模型和制动器逆模型的车辆逆动力学模型。最后针对ACC系统的功能需求,应用模型匹配控制理论设计能适应不同工况的鲁棒下层控制器,而上层控制器则通过线性二次最优控制理论获得综合考虑车距、相对速度和自车加速度的期望跟车加速度。仿真结果表明,该ACC系统能使车辆在加速行驶、稳态跟车和制动减速等行驶工况下保持良好的跟踪性和自适应性。     

基于车联网的行人主动避撞策略及仿真验证

针对行人从静止遮挡车辆前方穿出并与主车碰撞的“鬼探头”危险场景,提出一种基于车联网的行人主动避撞系统控制策略。首先,建立主车、遮挡车和行人间相对位置关系模型,通过车车通信获取遮挡车前方的行人状态信息;其次,根据目标进入时间、目标离开时间、碰撞剩余时间和安全避撞时间4个危险状态判断评价指标,建立分级制动策略,并通过下层PID控制调节制动压力实现车辆控制;最后,基于PreScan、CarSim和MATLAB联合仿真平台,搭建该危险场景并验证所提出控制策略的有效性。结果表明,该策略能够实现避撞功能,且性能优于基于宽度触发的行人主动避撞策略。     

自动紧急制动系统行人测试场景的研究

为建立适用于我国交通状况的AEB行人测试场景,参考国际上已有的研究成果,首先采集了上海道路中的典型行人危险工况,并筛选出52例车与行人冲突的工况样本,然后利用聚类分析的多元统计学方法对这些样本进行分析,得到了5类具有典型特征的危险场景;根据这些典型危险场景设计了兼容我国交通工况的AEB行人测试场景,并建立相应的PreScan仿真模型。通过PreScan仿真测试可在未进行实际场地测试前对AEB系统进行初步评价,进而降低开发成本。     

基于多模式切换的智能汽车自适应巡航控制研究

针对前车运动状态和驾驶意图的不可预知性导致传统自适应巡航控制(ACC)系统应用受限的问题,设计了一种多模式切换的自适应巡航控制方法。根据自车与前车的运动学关系划分行驶模式,采用紧急系数表征各行驶模式下的危险程度;设计模糊控制器调节模型预测控制(MPC)中目标函数的权重值,以满足不同工况下跟车性和舒适性的需求差异,实现不同控制模式间的切换。仿真结果表明,多模式切换控制方法有效提高了车辆跟车性和舒适性,在各种工况下取得了优良的控制效果。     

基于危险性的汽车ACC切车场景设计研究

针对汽车自适应巡航控制系统功能测试需求，基于曝光度及危险性分析设计ACC切车场景。基于自然驾驶数据，通过对切车工况数据特征进行分析，提取切车工况，并基于先验的智能驾驶模型、最优化方法和扫描线种子填充算法设计了关键切车场景。基于场景仿真软件完成了关键切车场景的构建及对ACC功能模块的仿真验证，并进行了危险切车场景仿真分析。结果表明基于考量场景曝光度及危险性的自然驾驶关键切车场景提取与设计方法，可有效设计开发汽车自适应巡航控制系统典型测试场景。     

Slip regulation for anti-lock braking systems using multiple surface sliding controller combined with inertial delay control

In this paper, a multiple surface sliding controller is designed for an anti-lock braking system to maintain the slip ratio at a desired level. Various types of uncertainties coming from unknown road surface conditions, the variations in normal force and the mass of the vehicle are estimated using an uncertainty estimation technique called the inertial delay control and then the estimate is used in the design of the multiple surface sliding controller. The proposed scheme does not require the bounds of uncertainties. The ultimate boundedness of the overall system is proved. The proposed scheme is validated by simulation under various scenarios of road friction, road gradient and vehicle loading followed by experimentation on a laboratory anti-lock braking set-up for different friction conditions.     

Real-time weighted multi-objective model predictive controller for adaptive cruise control systems

In this paper, a novel spacing control law is developed for vehicles with adaptive cruise control (ACC) systems to perform spacing control mode. Rather than establishing a steady-state following distance behind a newly encountered vehicle to avoid collision, the proposed spacing control law based on model predictive control (MPC) further considers fuel economy and ride comfort. Firstly, a hierarchical control architecture is utilized in which a lower controller compensates for nonlinear longitudinal vehicle dynamics and enables to track the desired acceleration. The upper controller based on the proposed spacing control law is designed to compute the desired acceleration to maintain the control objectives. Moreover, the control objectives are then formulated into the model predictive control problem using acceleration and jerk limits as constrains. Furthermore, due to the complex driving conditions during in the transitional state, the traditional model predictive control algorithm with constant weight matrix cannot meet the requirement of improvement in the fuel economy and ride comfort. Therefore, a real-time weight tuning strategy is proposed to solve time-varying multi-objective control problems, where the weight of each objective can be adjusted with respect to different operating conditions. In addition, simulation results demonstrate that the ACC system with the proposed real-time weighted MPC (RW-MPC) can provide better performance than that using constant weight MPC (CW-MPC) in terms of fuel economy and ride comfort.     

Vehicle stability control system for enhancing steerabilty,lateral stability,and roll stability

The Vehicle stability control system is an active safety system designed to prevent accidents from occurring and to stabilize dynamic maneuvers of a vehicle by generating an artificial yaw moment using differential brakes. In this paper, in order to enhance vehicle steerability, lateral stability, and roll stability, each reference yaw rate is designed and combined into a target yaw rate depending on the driving situation. A yaw rate controller is designed to track the target yaw rate based on sliding mode control theory. To generate the total yaw moment required from the proposed yaw rate controller, each brake pressure is properly distributed with effective control wheel decision. Estimators are developed to identify the roll angle and body sideslip angle of a vehicle based on the simplified roll dynamics model and parameter adaptation approach. The performance of the proposed vehicle stability control system and estimation algorithms is verified with simulation results and experimental results.     

An optimal torque distribution control strategy for four-independent wheel drive electric vehicles

In this paper, an optimal torque distribution approach is proposed for electric vehicle equipped with four independent wheel motors to improve vehicle handling and stability performance. A novel objective function is formulated which works in a multifunctional way by considering the interference among different performance indices: forces and moment errors at the centre of gravity of the vehicle, actuator control efforts and tyre workload usage. To adapt different driving conditions, a weighting factors tuning scheme is designed to adjust the relative weight of each performance in the objective function. The effectiveness of the proposed optimal torque distribution is evaluated by simulations with CarSim and Matlab/Simulink. The simulation results under different driving scenarios indicate that the proposed control strategy can effectively improve the vehicle handling and stability even in slippery road conditions.     

A comparative study on the power characteristics and control strategies for plug-in hybrid electric vehicles

A comparative study was performed on two types of plug-in hybrid electric vehicles (PHEVs): the GM Volt and the Toyota Prius Plug-in Hybrid. First, the powertrain models of the two vehicles were derived. Based on the dynamic models, a detailed component control algorithm was developed for each PHEV. Specifically, a control algorithm was proposed for motor generator 1 (MG1) and MG2 to achieve optimal engine operation. Additionally, an energy management strategy for selecting the operation mode was developed from the viewpoint of fuel economy, battery state of charge and vehicle velocity. Using the dynamic model of the control algorithm for each PHEV, simulations were performed, and the simulation results were verified by comparing them with those obtained using the Powertrain System Analysis Toolkit simulator for the plug-in Prius. Based on the simulation results, a comparative study was performed, and it was found that the role and capacity of MG1 and MG2 and the mode selection algorithm must be determined depending on the configuration of the PHEV.     

Fuzzy adaptive sliding mode controller for an air spring active suspension

A fuzzy adaptive sliding mode controller for an air spring active suspension system is developed. Due to nonlinearity, preload-dependent spring force and parameter uncertainty in the air spring, it is difficult to control the suspension system. To achieve the desired performance, a fuzzy adaptive sliding mode controller (FASMC) is designed to improve the passenger comfort and the manipulability of the vehicle. The fuzzy adaptive system handles the nonlinearity and uncertainty of the air suspension. A normal linear suspension model with an optimal state feedback control is designed as the reference model. The simulation results show that this control scheme more effectively and robustly isolates vibrations of the vehicle body than the conventional sliding mode controller (CSMC).     

Emergency steering control of autonomous vehicle for collision avoidance and stabilisation

ABSTRACT

Collision avoidance and stabilisation are two of the most crucial concerns when an autonomous vehicle finds itself in emergency situations, which usually occur in a short time horizon and require large actuator inputs, together with highly nonlinear tyre cornering response. In order to avoid collision while stabilising autonomous vehicle under dynamic driving situations at handling limits, this paper proposes a novel emergency steering control strategy based on hierarchical control architecture consisting of decision-making layer and motion control layer. In decision-making layer, a dynamic threat assessment model continuously evaluates the risk associated with collision and destabilisation, and a path planner based on kinematics and dynamics of vehicle system determines a collision-free path when it suddenly encounters emergency scenarios. In motion control layer, a lateral motion controller considering nonlinearity of tyre cornering response and unknown external disturbance is designed using tyre lateral force estimation-based backstepping sliding-mode control to track a collision-free path, and to ensure the robustness and stability of the closed-loop system. Both simulation and experiment results show that the proposed control scheme can effectively perform an emergency collision avoidance manoeuvre while maintaining the stability of autonomous vehicle in different running conditions.     

Design and validation of a longitudinal velocity and distance controller via hardware-in-the-loop simulation

In this paper, a set of longitudinal velocity and distance controllers with switching logic is proposed for an active driver safety system, and validation via hardware-in-the-loop simulation (HILS) is presented. Since the desired velocity and distance are given discretely and arbitrarily by a driver, there are usually discontinuities or discrete jumps between the desired and current vehicle state immediately after the switching. To minimize performance degradation resulting from this discrete jump, dynamic surface control (DSC) with an input-shaping filter is applied for both velocity and distance control. Furthermore, while much cost and effort are usually necessary for the experimental validation of a longitudinal controller, the validation of the longitudinal controller via HILS is performed with a minimum of effort. In the HILS, the various switching scenarios and desired discrete inputs in terms of velocity and distance are considered and the corresponding performance of the controller is shown in the end.     

基于双模式执行器的商用车自适应巡航控制系统

为实现商用车自适应巡航控制(ACC)系统的功能,开发了双模式制动执行装置和电子油门控制装置,即基于高速开关阀的商用车气压电控辅助制动系统和双模式油门控制系统,可以实现驾驶员和ACC系统的协同切换控制。在此基础上,以某商用车为对象,设计了ACC系统,结合比例-积分控制器和Smith预估补偿器设计了ACC的下位控制算法。结果表明:该ACC系统速度稳态跟踪误差小于1 m.s-1,距离稳态跟踪误差小于1.5 m;同时油门执行器和制动执行器具有安装方便、与原车电子油门及气压制动系统兼容性好的优点。