Design of safety-oriented control allocation strategies for overactuated electric vehicles

The new vehicle platforms for electric vehicles (EVs) that are becoming available are characterised by actuator redundancy, which makes it possible to jointly optimise different aspects of the vehicle motion. To do this, high-level control objectives are first specified and solved with appropriate control strategies. Then, the resulting virtual control action must be translated into actual actuator commands by a control allocation layer that takes care of computing the forces to be applied at the wheels. This step, in general, is quite demanding as far as computational complexity is considered. In this work, a safety-oriented approach to this problem is proposed. Specifically, a four-wheel steer EV with four in-wheel motors is considered, and the high-level motion controller is designed within a sliding mode framework with conditional integrators. For distributing the forces among the tyres, two control allocation approaches are investigated. The first, based on the extension of the cascading generalised inverse method, is computationally efficient but shows some limitations in dealing with unfeasible force values. To solve the problem, a second allocation algorithm is proposed, which relies on the linearisation of the tyre–road friction constraints. Extensive tests, carried out in the CarSim simulation environment, demonstrate the effectiveness of the proposed approach.     

人机混驾环境下无信号交叉口自动驾驶汽车左转运动规划研究

为了使自动驾驶汽车在人机混驾环境下能安全、高效地左转通过无信号交叉口，在借鉴人类驾驶人左转时会对周围车辆驾驶意图进行提前预判的基础上，提出了一种基于周围车辆驾驶意图预测的自动驾驶汽车左转运动规划模型。首先将无信号交叉口处周围车辆的驾驶意图分为左转、右转、直行3种类型，利用相关向量机预测周围车辆驾驶意图，以概率形式输出意图预测结果并实时更新，进一步界定自动驾驶汽车与周围车辆的潜在冲突区域并判断是否存在时空冲突；接着，在充分考虑他车速度、航向及车辆到达冲突区域边界距离的基础上建立基于部分可观测马尔可夫决策过程的自动驾驶汽车左转运动规划模型，生成一系列期望加速度；最后，基于Prescan-Simulink联合仿真平台搭建无信号交叉口仿真场景，对所提左转运动规划方法进行仿真验证，将基于博弈论的运动规划方法、基于人工势场理论的运动规划方法与所提出的方法进行比较，并选取行进比例达到1所用的时间和碰撞次数作为评价指标。研究结果表明：基于相关向量机的驾驶意图预测方法可在自动驾驶汽车到达交叉口之前准确预测出他车驾驶意图；基于部分可观测马尔可夫决策过程的左转运动规划方法能够通过速度调整策略实现人机混驾环境下自动驾驶汽车与周围车辆在无信号交叉口处的交互；不同算法对比效果表明，所提左转运动规划方法在自动驾驶汽车与不同数量周围车辆交互的仿真场景下均可有效避免碰撞事故发生并提高自动驾驶汽车左转通过无信号交叉口的效率。     

无人驾驶车辆解耦混合运动规划方法研究

高速公路无人驾驶车辆运动规划要充分考虑车辆的动力学特性和道路环境构成的复杂约束,优先确保车辆的无碰撞行驶轨迹,同时算法实时性比常速情况下要求更高,要充分考虑计算的复杂性。提出一种可生成横纵向最优解逼近群的解耦增强混合运动规划方法,引入Frent坐标系将运动规划问题进行横纵向解耦,在横向偏移规划中融合数值优化和多项式规划算法,在纵向速度规划中融合围绕速度和围绕避障规划算法,解耦规划完成后使用代价函数和碰撞检测方法对生成的轨迹群进行评估和选择。搭建Apollo-LGsvl无人驾驶联合仿真测试平台,对所提出的运动规划方法进行仿真验证。结果表明,提出的横纵向解耦增强混合运动规划算法在高速公路各工况中所生成的运动轨迹能够有效避免车辆发生碰撞,其横向偏移和纵向速度均能满足二阶平滑,最大横向加速度、最大纵向加速度、最大纵向jerk等满足动力学约束。该方法有效减少了最优解逼近群内的轨迹数量,使轨迹评估阶段计算复杂度降低了46%,证明提出的方法具备一定的应用价值。     

浅水淹车辆快速检修实例

随着国内经济的发展,人民生活水平不断提高,轿车已经作为代步工具,逐渐走进寻常百姓家。随着车辆的增多意外情形也不断增多,旅游户外车辆涉水情况就是其中之一,涉水车辆未辨明情况状态下,轻易不要启动车辆,否则会造成车辆更大伤害,同时还是影响保险赔付,一些情况下可以通过简单的判断就可启动车辆,不会对车辆造成更大伤害。文章针对未启动浅水淹车实例,介绍能够使用简单工具快速判断车辆状态,帮助车辆在救援不便时快速脱困,具有一定的实际意义。     

Automatic generation of the non-holonomic equations of motion for vehicle stability analysis

The mathematical analysis of vehicle stability has been utilised as an important tool in the design, development, and evaluation of vehicle architectures and stability controls. This paper presents a novel method for automatic generation of the linearised equations of motion for mechanical systems that is well suited to vehicle stability analysis. Unlike conventional methods for generating linearised equations of motion in standard linear second order form, the proposed method allows for the analysis of systems with non-holonomic constraints. In the proposed method, the algebraic constraint equations are eliminated after linearisation and reduction to first order. The described method has been successfully applied to an assortment of classic dynamic problems of varying complexity including the classic rolling coin, the planar truck–trailer, and the bicycle, as well as in more recent problems such as a rotor–stator and a benchmark road vehicle with suspension. This method has also been applied in the design and analysis of a novel three-wheeled narrow tilting vehicle with zero roll-stiffness. An application for determining passively stable configurations using the proposed method together with a genetic search algorithm is detailed. The proposed method and software implementation has been shown to be robust and provides invaluable conceptual insight into the stability of vehicles and mechanical systems.     

Flow-field guided steering control for rigid autonomous ground vehicles in low-speed manoeuvring

ABSTRACT

This paper studies the low-speed manoeuvring problem for autono-mous ground vehicles operating in complex static environments. Making use of the intrinsic property of a fluid to naturally find its way to an outflow destination, a novel guidance method is proposed. In this approach, a reference flow field is calculated numerically through Computational Fluid Dynamics, based on which both the reference path topology and the steering reference to achieve the path are derived in a single process. Steering control considers three constraints: obstacle and boundary avoidance, rigidity of the vehicle, plus the non-holonomic velocity constraints due to the steering system. The influences of the parameters used during the flow field simulation and the control algorithm are discussed through numerical cases. A divergency field is defined to evaluate the quality of the flow field in guiding the vehicle. This is used to identify any problematic branching features of the flow, and control is adapted in the neighbourhood of such branching features to resolve possible ambiguities in the control reference. Results demonstrate the effectiveness of the method in finding smooth and feasible motion paths, even in complex environments.     

Minimum-time manoeuvring in electric vehicles with four wheel-individual-motors

The coordinated control of vehicle actuators is gaining more and more importance as new platforms are becoming available, with chassis endowed with many different actuators that may help controlling the vehicle motion. Furthermore, wheel individual motors allow using a single system to apply both positive and negative torques at the wheels, which can be actuated independently one from the other. In electric vehicles (EVs), moreover, such a freedom in the actuation mechanisms opens the way to the combined optimisation of performance and energy consumption issues. In this paper, the problem of minimum-time manoeuvring in EVs is addressed, and the proposed strategy is compared against a benchmark, a-causal optimal solution showing that only a negligible loss of performance is experienced.     

信号交叉口自动驾驶左转车辆类人化全局运动轨迹规划

为了提高信号交叉口自动驾驶车辆左转运动规划的适应性、鲁棒性与类人化程度，提出一种考虑多目标需求的自动驾驶类人化全局运动规划方法。首先，基于西安市北大街信号交叉口规格构建结构化场景，结合车辆运动学模型与道路几何规格定义自动驾驶车辆规范化行驶安全域和车辆运动参数约束条件；其次，根据信号灯状态、道路限速与车辆性能约束制定上游阶段车辆不停车通行规则，以行驶安全、燃油消耗、通行效率与驾驶舒适度作为目标性能函数，构建类人化全局多目标优化模型，通过人类驾驶的车辆预转弯行为耦合上游阶段与转弯阶段；再次，针对非线性运动规划模型变量与约束规模化问题，采用粒子群算法与全联立正交配置有限元方法求解不同阶段车辆运动轨迹的最优解；最后，试验建立Prescan与MATLAB/Simulink联合仿真平台，从多目标性能、适应性以及合理性方面验证该模型的综合性能。结果表明：在以信号灯状态和车辆初速度为变量建立的12种工况下，该模型与人类驾驶车辆、混合运动规划模型相比，平均可分别节省燃油消耗63.7%和29.5%，平均通行延时分别降低3、0.9 s，且轨迹曲率更平缓，最大横向加速度与方向盘转角平方和的平均值最小，证明该模型的多目标性能更好；在以路缘石半径与车道数目为变量建立的7种交叉口规格工况下，所提出模型的车辆轨迹平滑，轨迹安全域边界距离始终大于1.4 m，曲率变化符合期望且峰值小于0.22 m^-1，说明该模型具有较好的适应性；在自由/固定终端时刻条件下，该模型规划的车辆空间路径、速度、曲率及航向角的变化与目标权重变化保持一致，验证了模型的合理性。     

Two-Dimensional Motion of Vehicles Damaged due to Collision

This paper deals with two-dimensional motion analysis of vehicles damaged due to collision. Various parts of vehicles are damaged due to collision in general. The effects of the damage in vehicle body and wheels on the vehicle motions are investigated. The center of gravity of the vehicle and the polar moment of inertia are changed by the deformation of vehicle body. Furthermore, the geometrical relations of wheels like wheelbase, treads and steering angles may be changed by damage of the wheels. Thus the vehicle loses symmetry with respect to the vehicle axis. The four-wheel vehicle model is extended to take into account the vehicle damage due to collision. The motions of damaged vehicles are compared with those of undamaged vehicles. It is found that vehicle damages have a significant influence on vehicle motion after impact.     

Two-Dimensional Motion of Vehicles Damaged due to Collision

This paper deals with two-dimensional motion analysis of vehicles damaged due to collision. Various parts of vehicles are damaged due to collision in general. The effects of the damage in vehicle body and wheels on the vehicle motions are investigated. The center of gravity of the vehicle and the polar moment of inertia are changed by the deformation of vehicle body. Furthermore, the geometrical relations of wheels like wheelbase, treads and steering angles may be changed by damage of the wheels. Thus the vehicle loses symmetry with respect to the vehicle axis. The four-wheel vehicle model is extended to take into account the vehicle damage due to collision. The motions of damaged vehicles are compared with those of undamaged vehicles. It is found that vehicle damages have a significant influence on vehicle motion after impact.     

A study on model fidelity for model predictive control-based obstacle avoidance in high-speed autonomous ground vehicles

This paper investigates the level of model fidelity needed in order for a model predictive control (MPC)-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. The context of this work is large autonomous ground vehicles that manoeuvre at high speed within unknown, unstructured, flat environments and have significant vehicle dynamics-related constraints. Five different representations of vehicle dynamics models are considered: four variations of the two degrees-of-freedom (DoF) representation as lower fidelity models and a fourteen DoF representation with combined-slip Magic Formula tyre model as a higher fidelity model. It is concluded that the two DoF representation that accounts for tyre nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm in order to operate the vehicle at its limits within an environment that includes large obstacles. For less challenging environments, however, the two DoF representation with linear tyre model and constant axle loads is sufficient.     

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.     

Real-time capable vehicle–trailer coupling by algorithms for differential-algebraic equations

The real-time simulation of vehicle trains requires an accurate and numerically feasible representation of the vehicle–trailer coupling. Although the equations of motion for the chassis instances can be reduced to systems of ordinary differential equations, additional constraints on the relative motion of vehicle and trailer are introduced when considering the hitch. In this article, we present a strategy for the simulation of vehicle–trailer combinations, where the algebraic constraints of the coupling are treated explicitly. Although this approach allows exact modeling of the respective joint geometry and realistic calculation of the coupling forces, a suitable numerical algorithm is required in order to solve the resulting differential-algebraic system of index 3 in real-time. The implementation in a commercial vehicle dynamics program is discussed and real-time simulation results are shown, which prove its feasibility for different coupling joints and demanding driving maneuvers.     

An improvement in rollover detection of articulated vehicles using the grey system theory

A Rollover Index combined with the grey system theory, called a Grey Rollover Index (GRI), is proposed to assess the rollover threat for articulated vehicles with a tractor–semitrailer combination. This index can predict future trends of vehicle dynamics based on current vehicle motion; thus, it is suitable for vehicle-rollover detection. Two difficulties are encountered when applying the GRI for rollover detection. The first difficulty is effectively predicting the rollover threat of the vehicles, and the second difficulty is achieving a definite definition of the real rollover timing of a vehicle. The following methods are used to resolve these problems. First, a nonlinear mathematical model is constructed to accurately describe the vehicle dynamics of articulated vehicles. This model is combined with the GRI to predict rollover propensity. Finally, TruckSim^? software is used to determine the real rollover timing and facilitate the accurate supply of information to the rollover detection system through the GRI. This index is used to verify the simulation based on the common manoeuvres that cause rollover accidents to reduce the occurrence of false signals and effectively increase the efficiency of the rollover detection system.     

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.     

Kinematic design of double-wishbone suspension systems using a multiobjective optimisation approach

This paper is focused on the kinematic design of double-wishbone suspension systems in vehicles, which is tackled using a multiobjective dimensional synthesis technique. The synthesis goal is to optimise an RSSR–SS linkage, subject to some constraints involved in the dynamic behaviour of vehicles. The synthesis method is based on gradient determination using exact differentiation to obtain the elements in the Jacobian matrix. These characteristics make the method adapt well to the optimum design of vehicle suspension systems. The method is capable of handling equality and inequality constraints, thus, the usual ranges of values may be imposed on the functional parameters. The formulation presented is easy to implement and the solutions obtained demonstrate the accuracy and robustness of the method.     

Collaborative merging strategy for freeway ramp operations in a connected and autonomous vehicles environment

In a connected vehicle environment, vehicles are able to communicate and exchange detailed information such as speed, acceleration, and position in real time. Such information exchange is important for improving traffic safety and mobility. This allows vehicles to collaborate with each other, which can significantly improve traffic operations particularly at intersections and freeway ramps. To assess the potential safety and mobility benefits of collaborative driving enabled by connected vehicle technologies, this study developed an optimization-based ramp control strategy and a simulation evaluation platform using VISSIM, MATLAB, and the Car2X module in VISSIM. The ramp control strategy is formulated as a constrained nonlinear optimization problem and solved by the MATLAB optimization toolbox. The optimization model provides individual vehicles with step-by-step control instructions in the ramp merging area. In addition to the optimization-based ramp control strategy, an empirical gradual speed limit control strategy is also formulated. These strategies are evaluated using the developed simulation platform in terms of average speed, average delay time, and throughput and are compared with a benchmark case with no control. The study results indicate that the proposed optimal control strategy can effectively coordinate merging vehicles at freeway on-ramps and substantially improve safety and mobility, especially when the freeway traffic is not oversaturated. The ramp control strategy can be further extended to improve traffic operations at bottlenecks caused by incidents, which cause approximately 25% of traffic congestion in the United States.     

Fault classification method for the driving safety of electrified vehicles

A fault classification method is proposed which has been applied to an electric vehicle. Potential faults in the different subsystems that can affect the vehicle directional stability were collected in a failure mode and effect analysis. Similar driveline faults were grouped together if they resembled each other with respect to their influence on the vehicle dynamic behaviour. The faults were physically modelled in a simulation environment before they were induced in a detailed vehicle model under normal driving conditions. A special focus was placed on faults in the driveline of electric vehicles employing in-wheel motors of the permanent magnet type. Several failures caused by mechanical and other faults were analysed as well. The fault classification method consists of a controllability ranking developed according to the functional safety standard ISO 26262. The controllability of a fault was determined with three parameters covering the influence of the longitudinal, lateral and yaw motion of the vehicle. The simulation results were analysed and the faults were classified according to their controllability using the proposed method. It was shown that the controllability decreased specifically with increasing lateral acceleration and increasing speed. The results for the electric driveline faults show that this trend cannot be generalised for all the faults, as the controllability deteriorated for some faults during manoeuvres with low lateral acceleration and low speed. The proposed method is generic and can be applied to various other types of road vehicles and faults.     

A tube-based robust nonlinear predictive control approach to semiautonomous ground vehicles

This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents a systematic way of enforcing robustness during the MPC design stage. A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre line. A force-input nonlinear bicycle vehicle model is developed and used in the RNMPC control design. A robust invariant set is used in the RNMPC design to guarantee that state and input constraints are satisfied in the presence of disturbances and model error. Simulations and experiments on a vehicle show the effectiveness of the proposed framework.