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.     

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.     

Human driving data-based design of a vehicle adaptive cruise control algorithm

This paper presents a vehicle adaptive cruise control algorithm design with human factors considerations. Adaptive cruise control (ACC) systems should be acceptable to drivers. In order to be acceptable to drivers, the ACC systems need to be designed based on the analysis of human driver driving behaviour. Manual driving characteristics are investigated using real-world driving test data. The goal of the control algorithm is to achieve naturalistic behaviour of the controlled vehicle that would feel natural to the human driver in normal driving situations and to achieve safe vehicle behaviour in severe braking situations in which large decelerations are necessary. A non-dimensional warning index and inverse time-to-collision are used to evaluate driving situations. A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC system. Using a simulation and a validated vehicle simulator, vehicle following characteristics of the controlled vehicle are compared with real-world manual driving radar sensor data. It is shown that the proposed control strategy can provide with natural following performance similar to human manual driving in both high speed driving and low speed stop-and-go situations and can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.     

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.     

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。     

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.     

基于ADAMS整车操纵稳定性分析

利用ADAMS软件，建立整车模型。对整车进行操纵稳定性分析，包括稳态回转、角跃阶输入、低速与高速转向回正以及单移线试验。从而实现了虚拟样机技术的应用，仿真分析整车的操纵稳定性，也验证了模型建立的准确性。     

Heavy-duty vehicle modelling and longitudinal control

This paper addresses modelling, longitudinal control design and implementation for heavy-duty vehicles (HDVs). The challenging problems here are: (a) an HDV is mass dominant with low power to mass ratio; (b) They possess large actuator delay and actuator saturation. To reduce model mismatch, it is necessary to obtain a nonlinear model which is as simple as the control design method can handle and as complicated as necessary to capture the intrinsic vehicle dynamics. A second order nonlinear vehicle body dynamical model is adopted, which is feedback linearizable. Beside the vehicle dynamics, other main dynamical components along the power-train and drive-train are also modelled, which include turbocharged diesel engine, torque converter, transmission, transmission retarder, pneumatic brake and tyre. The braking system is the most challenging part for control design, which contains three parts: Jake (engine compression) brake, air brake and transmission retarder. The modelling for each is provided. The use of engine braking effect is new complementary to Jake (compression) brake for longitudinal control, which is united with Jake brake in modelling. The control structure can be divided into upper level and lower level. Upper level control uses sliding mode control to generate the desired torque from the desired vehicle acceleration. Lower level control is divided into two branches: (a) engine control: from positive desired torque to desired fuel rate (engine control) using a static engine mapping which basically captures the intrinsic dynamic performance of the turbo-charged diesel engine; (b) brake control: from desired negative torque to generate Jake brake cylinder number to be activated and ON/OFF time periods, applied pneumatic brake pressure and applied voltage of transmission retarder. Test results are also reported.     

Heavy-duty vehicle modelling and longitudinal control

This paper addresses modelling, longitudinal control design and implementation for heavy-duty vehicles (HDVs). The challenging problems here are: (a) an HDV is mass dominant with low power to mass ratio; (b) They possess large actuator delay and actuator saturation. To reduce model mismatch, it is necessary to obtain a nonlinear model which is as simple as the control design method can handle and as complicated as necessary to capture the intrinsic vehicle dynamics. A second order nonlinear vehicle body dynamical model is adopted, which is feedback linearizable. Beside the vehicle dynamics, other main dynamical components along the power-train and drive-train are also modelled, which include turbocharged diesel engine, torque converter, transmission, transmission retarder, pneumatic brake and tyre. The braking system is the most challenging part for control design, which contains three parts: Jake (engine compression) brake, air brake and transmission retarder. The modelling for each is provided. The use of engine braking effect is new complementary to Jake (compression) brake for longitudinal control, which is united with Jake brake in modelling. The control structure can be divided into upper level and lower level. Upper level control uses sliding mode control to generate the desired torque from the desired vehicle acceleration. Lower level control is divided into two branches: (a) engine control: from positive desired torque to desired fuel rate (engine control) using a static engine mapping which basically captures the intrinsic dynamic performance of the turbo-charged diesel engine; (b) brake control: from desired negative torque to generate Jake brake cylinder number to be activated and ON/OFF time periods, applied pneumatic brake pressure and applied voltage of transmission retarder. Test results are also reported.     

Optimal roll control of an articulated vehicle: theory and model validation

This paper investigates optimal roll control of an experimental articulated vehicle. The test vehicle and the mathematical model used to design the control strategies are presented. The vehicle model is validated against experimental data from the test vehicle in passive configuration. The initial controller design, performed by Sampson (Sampson, D.J.M. and Cebon, D., 2003a, Achievable roll stability of heavy road vehicles. Proc. Instn. Mech. Engrs, Part D, J. Automobile Engineering, 217(4), 269–287), is reviewed and adapted for the experimental vehicle. The effect of not controlling all the axles on the vehicle is investigated and a variable vehicle speed controller is designed by interpolating between constant speed controllers. Substantial reduction in normalized load transfer is achieved for a range of manoeuvres, both in steady-state and transient conditions.     

Optimal roll control of an articulated vehicle: theory and model validation

This paper investigates optimal roll control of an experimental articulated vehicle. The test vehicle and the mathematical model used to design the control strategies are presented. The vehicle model is validated against experimental data from the test vehicle in passive configuration. The initial controller design, performed by Sampson (Sampson, D.J.M. and Cebon, D., 2003a, Achievable roll stability of heavy road vehicles. Proc. Instn. Mech. Engrs, Part D, J. Automobile Engineering, 217(4), 269-287), is reviewed and adapted for the experimental vehicle. The effect of not controlling all the axles on the vehicle is investigated and a variable vehicle speed controller is designed by interpolating between constant speed controllers. Substantial reduction in normalized load transfer is achieved for a range of manoeuvres, both in steady-state and transient conditions.     

Design of a headway distance control system for ACC

A headway distance control system for adaptive cruise control (ACC) must provide the driver's desired response at all times while maintaining stability. Therefore, a two- degree-of-freedom model was adopted for the headway distance control unit to allow response and stability to be designed as independent parameters. The desired response was decided based on the results of various driving tests and driving simulations. Using these results as the reference model has achieved the smooth response and stability required for ACC.     

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。     

Numerical investigation of engine-to-slip dynamics for motorcycle traction control applications

This work discusses the motorcycle engine-to-slip dynamics which are strictly related to the traction control design. A street motorcycle is analysed by means of an advanced mathematical model which also includes the tyre flexibility and the transmission compliance. The effects of the following parameters on engine-to-slip dynamics are investigated: vehicle speed, engaged gear ratio, sprocket absorber flexibility and road properties. Guidelines for increasing the maximum achievable closed-loop bandwidth are given.     

Robust control and actuator dynamics compensation for railway vehicles

A robust controller is designed for active steering of a high speed train bogie with solid axle wheel sets to reduce track irregularity effects on the vehicle’s dynamics and improve stability and curving performance. A half-car railway vehicle model with seven degrees of freedom equipped with practical accelerometers and angular velocity sensors is considered for the H_∞ control design. The controller is robust against the wheel/rail contact parameter variations. Field measurement data are used as the track irregularities in simulations. The control force is applied to the vehicle model via ball-screw electromechanical actuators. To compensate the actuator dynamics, the time delay is identified online and is used in a second-order polynomial extrapolation carried out to predict and modify the control command to the actuator. The performance of the proposed controller and actuator dynamics compensation technique are examined on a one-car railway vehicle model with realistic structural parameters and nonlinear wheel and rail profiles. The results showed that for the case of nonlinear wheel and rail profiles significant improvements in the active control performance can be achieved using the proposed compensation technique.     

多电机电动车动力学系统隐模型跟踪控制

提出一种应用隐模型跟踪最优二次型调节器的车辆动力学控制方法,为多电机独立驱动电动车设计了直接横摆力偶矩控制器,通过仿真计算证明了该控制方法的有效性。     

Lane-keeping benefits of practical rear axle steer

The classic two-degree-of-freedom yaw-plane or ‘bicycle’ vehicle model is augmented with two additional states to describe lane-keeping behaviour and further augmented with an additional control input to steer the rear axle. A simple driver model is hypothesised where the driver closes a loop on a projected lateral lane position. The driver can select the preview distance to compensate driver/vehicle dynamics, consistent with the ‘cross-over’ model found in the literature. A rear axle steer control law is found to be a function of the front axle steering input and vehicle speed that exhibits stability similar to a positive-real system, while at the same time improving the ability of the driver/vehicle system to track a complex curved lane and improving steady-state manoeuvrability. The theoretically derived control law bears similarity to practical embodiments allowing a deeper understanding of the functional value of steering a rear axle.     

基于非线性模型预测控制的车辆纵向队列协调控制

本文中针对基于分层控制结构的车辆队列上、下层控制缺少联系的问题,提出了车辆队列跟驰与个体车辆动力学稳定性协调控制的思路,其基本思想是在保证队列中个体车辆安全稳定行驶的同时,尽可能实现队列跟驰控制的目标。基于非线性模型预测控制(nonlinear model predictive control,NMPC)方法设计了车辆队列协调控制方案,设计了包括跟驰间距误差、跟驰速度误差以及车速与车轮圆周速度差3个子目标的优化目标函数,将队列跟驰与车辆动力学稳定性的协调控制转化为约束优化控制问题;基于序列二次规划(sequential quadratic programming,SQP)方法进行求解,得到车辆前、后轴的制动/驱动力矩来实现上层决策输出的期望跟驰加速度。基于由3车辆组成的非线性队列模型对控制方案进行了仿真分析,结果表明,所提出的基于NMPC的车辆队列协调控制策略可以在大范围操纵工况下,在保证车辆安全稳定行驶的基础上实现队列的跟驰控制。     

Stability control of 4WS vehicles using robust IMC techniques

A robust nonparametric approach to vehicle stability control by means of a four-wheel steer by wire system is introduced. Both yaw rate and sideslip angle feedbacks are used in order to effectively take into account safety as well as handling performances. Reference courses for yaw rate and sideslip angle are computed on the basis of the vehicle speed and the handwheel angle imposed by the driver. An output multiplicative model set is used to describe the uncertainty arising from a wide range of vehicle operating situations. The effects of saturation of the control variables (i.e. front and rear steering angles) are taken into account by adopting enhanced internal model control methodologies in the design of the feedback controller. Actuator dynamics are considered in the controller design. Improvements on understeer characteristics, stability in demanding conditions such as turning on low friction surfaces, damping properties in impulsive manoeuvres, and improved handling in closed loop (i.e. with driver feedback) manoeuvres are shown through extensive simulation results performed on an accurate 14 degrees of freedom nonlinear model, which proved to give good modelling results as compared with collected experimental data.     

Optimisation of active suspension control inputs for improved vehicle handling performance

Active suspension is commonly considered under the framework of vertical vehicle dynamics control aimed at improvements in ride comfort. This paper uses a collocation-type control variable optimisation tool to investigate to which extent the fully active suspension (FAS) application can be broaden to the task of vehicle handling/cornering control. The optimisation approach is firstly applied to solely FAS actuator configurations and three types of double lane-change manoeuvres. The obtained optimisation results are used to gain insights into different control mechanisms that are used by FAS to improve the handling performance in terms of path following error reduction. For the same manoeuvres the FAS performance is compared with the performance of different active steering and active differential actuators. The optimisation study is finally extended to combined FAS and active front- and/or rear-steering configurations to investigate if they can use their complementary control authorities (over the vertical and lateral vehicle dynamics, respectively) to further improve the handling performance.