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.     

Sensorless adaptive speed control of a permanent-magnet dc motor for anti-lock brake systems

An adaptive control algorithm was developed for the sensorless speed control of a permanent-magnet DC motor directly connected to the hydraulic pump of an antilock brake system. Due to the severe cost and reliability constraints of the application, the motor speed was controlled by a very simple on-off switching method, in which the only measurement required is the voltage across the control switch. The motor speed was calculated solely from the back-EMF voltage during the period of the control cycle when the switching controller is in the switch-off mode. The stability of the developed adaptiveswitching control algorithm was proven mathematically and confirmed experimentally in several vehicle tests over a wide range of target speeds and pump-load conditions. The accuracy and the response time of the controller can easily be tuned by adjusting a single tuning parameter. The switching frequency of the controller can also easily be tuned by adjusting the over-and undershoot thresholds independently from the accuracy of the speed-tracking control.     

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.     

基于混杂理论的电磁与摩擦集成制动方法

鉴于传统电子液压制动系统连续制动易产生"热衰退"现象，结构缺陷导致的制动响应慢，制动系统与电控系统衔接差等缺点，提出了一种基于混杂自动机模型的电磁与摩擦集成制动方法。首先分析集成制动器制动时的工作特点以及不同情况下对应的工作模式（纯电磁制动、纯摩擦制动以及集成制动），并确定3种制动模式的切换条件，通过逻辑门限算法将其实现。根据制动时车辆既具有连续运动状态又有离散状态的混杂特性，使用MATLAB/Stateflow建立基于制动模式切换系统的推广自动机模型，并根据制动模式切换控制策略，对3种制动模式切换进行试验，验证制动模式切换控制策略的合理性。最后选取车辆制动初速度为28 m·s^-1的直线制动工况，分别在高附着系数（0.85）以及低附着系数（0.3）的路面条件下，通过试验平台对控制算法和制动系统性能进行试验验证。研究结果表明：所提出的汽车混杂理论模型以及优化方法在在低附着系数（0.3）路面条件下，集成制动方法较传统液压制动系统缩短5.12%的制动距离，缩短制动时间0.3 s；在高附着系数（0.85）路面条件下，集成制动方法较传统液压制动系统缩短5.66%的制动距离，缩短制动时间0.2 s，能有效提高制动效能。     

Practical vehicle rollover avoidance control using energy method

In this paper, a novel rollover prevention control algorithm is developed for application on vehicles with a high centre of gravity. The developed algorithm can be implemented on any vehicle equipped with an electronic stability program with or without an extra roll rate sensor. The vehicle rollover index is defined from the vehicle lateral kinetic energy and the new concept of virtual gravity. The algorithm is implemented on a production hydraulic control unit and tested using a typical medium size sport utility vehicle up to a speed of 110 km h^-1. The test results show that the control algorithm prevents the vehicle rollover very successfully without any noticeable false activation or over correction resulting in severe under steer. Also, the controlled wheel speed shows a very stable and smooth trace.     

Automated Vehicle Merging Maneuver Implementation for AHS

Summary This paper presents a real-time implementation of a general merging algorithm for automated highway systems. A merging control problem is proposed first. A real-time algorithm is then presented, which is used to calculate a smooth reference speed trajectory for the merging vehicle based on the speed of the main lane vehicle. This algorithm can also be applied even when the main lane vehicles change speed. To make the algorithm adapt to different road layouts and to increase safety, a concept of virtual platooning is proposed. It effectively shifts the time of platoon formation forward prior to the start of real merging. Aspects closely related to real-time implementation are discussed, such as the controller adopted, the use of magnetometer based distance measurement and information passing by communication from main lane vehicles. Test results are presented and briefly analyzed.     

Development of a rear-end collision avoidance system with automatic brake control

We have studied active safety technologies from the standpoint of “collision avoidance”. This paper describes a rear-end collision avoidance system with automatic brake control, which avoids a collision to the vehicle in front caused by inadvertent human errors using automatic emergency braking. The system is comprised of four key technological elements, headway distance measurement using scanning laser radar, path estimation algorithm with vehicle dynamics, collision prediction to the vehicle in front by a safe/danger decision algorithm, and longitudinal automatic brake control.     

汽车多普勒测速系统

提出了一种利用多普勒雷达检测车速、车距的系统方案。对系统主要参数进行了论证，并给出了主要电路的设计方法。本系统可安装于汽车上，用于雾天或夜间监测前方汽车，并在车速、车距达到安全边界时给出报警信号，以避免交通事故的发生。     

基于智能电动汽车的纵向车速跟随控制策略

首先,设计了一种切换缓冲区间阈值可调的切换逻辑。其次,设计了一种对车速变化具有自适应性的PI控制驱动策略,再次,设计一种基于模糊控制的制动控制策略,在保证纵向车速跟踪精度的前提下,能避免车辆制动时的“前冲现象”,提高了舒适性。最后,通过Matlab与Carsim、Amesim的联合仿真验证了算法的有效性。     

基于扰动观测的智能驾驶主动抗扰纵向车速控制算法

为了减少智能驾驶车辆的纵向车速控制的时滞,提高主动抗扰性,提出一种基于扰动观测的纵向车速控制算法,并进行了实车验证。模型中,采用前馈控制模块,并提前输出控制量,来提高车速跟随的响应性;以主动抗扰控制(ADRC)模块作为反馈环节,采用扩张状态观测器(ESO)在线估计内外部扰动,并在控制端进行补偿,实现了对车速的精确闭环控制。在弯道、环岛等路况下进行了实车实验。结果表明:该算法可以在5 s内控制车速从怠速快速跟踪到目标车速,总体平均误差为0.17 km/h。因而,该算法较传统的比例积分微分(PID)有更好的响应性、控制精度和抗扰性。     

无人驾驶机器人车辆非线性模糊滑模车速控制

为了实现不同行驶工况下车速的精确、稳定控制,提出一种基于非线性干扰观测器的无人驾驶机器人车辆模糊滑模车速控制方法。考虑模型不确定性和外部干扰对车速控制的影响,建立车辆纵向动力学模型。通过分析无人驾驶机器人油门机械腿、制动机械腿的结构、机械腿操纵自动挡车辆踏板的运动,建立油门机械腿和制动机械腿的运动学模型。在此基础上,分别设计油门/制动切换控制器、油门模糊滑模控制器以及制动模糊滑模控制器,并进行控制系统的稳定性分析。油门/制动切换控制器以目标车速的导数为输入来进行油门与制动之间的切换控制。油门模糊滑模控制器和制动模糊滑模控制器以当前车速以及车速误差为输入,分别以油门机械腿直线电机位移和制动机械腿直线电机位移为输出来实现对油门与制动的控制。模糊滑模控制器中,为了减少控制抖振,滑模控制的反馈增益系数由模糊逻辑进行在线调节。模糊滑模控制器中的非线性干扰观测器用于估计和补偿无人驾驶机器人车辆的模型不确定性与外部干扰。仿真及试验结果对比分析表明：本文方法能够精确地估计和补偿无人驾驶机器人车辆的模型不确定性和外部干扰,避免了油门控制与制动控制之间的频繁切换,并实现了精确稳定的车速控制。     

Shifting control of an automated mechanical transmission without using the clutch

The automated mechanical transmission (AMT) is gaining popularity in the automotive industry, due to its combination of the advantages of mechanical transmissions (MT) and automatic transmissions (AT) in terms of fuel consumption, low cost, improved driving comfort and shifting quality. However, the inherent structural characteristics of the AMT lead to disadvantages, including excessive wear of the clutch plates and jerk and traction interruption during the shift process, that severely affect its popularity in the automatic transmission industry. The emerging technology of shifting control without the use of the clutch is a promising way to improve the shifting transients of AMTs. This paper proposes a control algorithm that combines speed and torque control of the AMT vehicle powertrain to achieve shifting control without using the clutch. The key technologies of accurate engine torque and speed control and rapid position control of the shift actuators are described in detail. To realize accurate engine speed control, a combined control algorithm based on feed-forward, bang-bang and PID control is adopted. Additionally, an optimized closed-loop position control algorithm based on LQR is proposed for the shift actuators. The coordinated control algorithm based on engine and shift actuator control is described in detail and validated on a test vehicle equipped with an AMT. The results show that the coordinated control algorithm can achieve shifting control without the use of the clutch to improve driving comfort significantly, reduce shift transients and extend the service life of the clutch.     

Evaluation of preview G-Vectoring control to decelerate a vehicle prior to entry into a curve

This paper describes the development of the braking assistance system based on a “G-Vectoring” concept. The present work focuses in particular on “Preview G-Vectoring Control” (PGVC), which is based on the “G-Vectoring Control” (GVC) scheme. In GVC, the longitudinal-acceleration control algorithm is based on the actual lateral jerk. PGVC decelerates a vehicle before it enters a curve, and is based on a new longitudinal-acceleration control algorithm which uses predicted and actual lateral jerk. Using the predicted lateral jerk makes it possible to decelerate the vehicle prior to curve entry. This deceleration can emulate a driver’s deceleration as the vehicle approaches a curve entry. PGVC is based on such deceleration algorithms and enables automatic deceleration similar to the action of a driver. It is thus possible to significantly improve the driver’s feeling when this system is activated. Driving tests with this new control system on snowy-winding course confirmed that the automatic brake control quality improved considerably compared to manual driver control considering both lap time and ride quality. These results indicate that PGVC can be a useful braking assistance system not only to improve the driver’s handling performance but also to reduce the brake-task during driving on winding roads.     

Development of an autonomous braking system using the predicted stopping distance

An autonomous braking system is designed using the prediction of the stopping distance. The stopping distance needs to be determined by considering several factors such as the desired deceleration and the speed of the hydraulic brake actuator. In particular, the actuator speed is very critical because it affects the shape of the deceleration response and it determines the accuracy of the predicted stopping distance. The autonomous braking control algorithm is designed based on the predicted stopping distance. The proposed autonomous braking system has been validated in autonomous vehicle tests and demonstrates that the subject vehicle can avoid the collision effectively.     

纯电动客车整车驱动控制分析与研究

针对纯电动客车系统方案,分析了整车驱动控制策略,包括加速转矩控制、制动能量回馈、驻坡、怠速爬行等功能,以满足整车驾驶性能要求。     

Robust control of anti-lock brake system

A robust control algorithm for an anti-lock brake system is proposed. The method used is based on static-state feedback of longitudinal slip and does not involve controller scheduling with changing vehicle speed or road adhesion coefficient estimation. An improvement involving scheduling of longitudinal slip reference with longitudinal acceleration measurement is included. Electromechanical braking actuators are used in simulations, and the algorithm used in this study is shown to have high performance on roads with constant and varying adhesion coefficients, displaying nice robustness properties against large vehicle speed and road adhesion coefficient variations. Guidelines are provided for tuning controller gains to cope with unknown actuator delay and measurement noise.     

A tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel independent brake from moderate driving to limit handling

This paper presents a tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel braking for enhanced performance from moderate driving to limit handling. The proposed algorithm adopted hierarchical structure: supervisor – desired motion tracking controller – optimisation-based control allocation. In the supervisor, by considering transient cornering characteristics, desired vehicle motion is calculated. In the desired motion tracking controller, in order to track desired vehicle motion, virtual control input is determined in the manner of sliding mode control. In the control allocation, virtual control input is allocated to minimise cost function. The cost function consists of two major parts. First part is a slip-based tyre friction utilisation quantification, which does not need a tyre force estimation. Second part is an allocation guideline, which guides optimally allocated inputs to predefined solution. The proposed algorithm has been investigated via simulation from moderate driving to limit handling scenario. Compared to Base and direct yaw moment control system, the proposed algorithm can effectively reduce tyre dissipation energy in the moderate driving situation. Moreover, the proposed algorithm enhances limit handling performance compared to Base and direct yaw moment control system. In addition to comparison with Base and direct yaw moment control, comparison the proposed algorithm with the control algorithm based on the known tyre force information has been conducted. The results show that the performance of the proposed algorithm is similar with that of the control algorithm with the known tyre force information.     

A study of the environmental impacts of intelligent automated vehicle control at intersections via V2V and V2I communications

This article presents a novel intersection traffic management system for automated vehicles and quantifies its impact on fuel consumption and greenhouse gas emissions of CO₂ relative to traditional traffic signal and roundabout intersection control. The developed intelligent traffic management (ITM) techniques, which are based on a spatiotemporal reservation scheme, ensure that vehicles proceed through the intersection without colliding with other vehicles while at the same time reducing the intersection delay and environmental impacts. Specifically, the spatiotemporal reservation scheme provides each vehicle a collision-free path that is decomposed into a speed profile along with navigational instructions. The integration of the developed microscopic traffic simulator with instantaneous emission model, provides improved assessments of the environmental impact of traffic control strategies at intersections. The simulator architecture integrates several ITM algorithms, vehicle sensors, V2V/V2I communications, and emission and fuel consumption models. Each vehicle is modeled by an agent and each agent provides information depending on the specific vehicle sensors. The ITM system is supported by V2V and V2I communications, allowing the exchange of information among vehicles and infrastructure. The data include the estimated vehicle position and speed. Compared with traditional traffic management techniques, the simulation results prove that the proposed ITM system reduces CO₂ emissions significantly. The research also shows that these reductions are more significant when the traffic flow increases.     

A statistical process control approach using cumulative sum control chart analysis for traffic data quality verification and sensor calibration for weigh-in-motion systems

Weigh-in-motion systems have been widely used by state agencies to collect the traffic data on major state roadways and bridges to support traffic load forecasting, pavement design and analysis, infrastructure investment decision making, and transportation planning. However, the weigh-in-motion system itself poses difficulties in obtaining accurate data due to sensor characteristics that can be sensitive to vehicle speed, weather conditions, and changes in surrounding pavement conditions. This study focuses on developing a systematic methodology to detect weigh-in-motion sensor bias and enhance current practices for weigh-in-motion calibration. A mixture modeling technique using an expectation maximization algorithm was developed to divide the vehicle class 9 gross vehicle weight into three normally distributed components: unloaded, partially loaded, and fully loaded trucks. Then the well-known statistical process control technique cumulative sum control chart analysis was applied to expectation maximization estimates of daily mean gross vehicle weight for fully loaded trucks to identify and estimate shifts in the weigh-in-motion sensor. Special attention was given to the presence of autocorrelation in the data by fitting an autoregressive time-series model and then performing cumulative sum control chart analysis on the fitted residuals. Results from the analysis suggest that the proposed methodology is able to estimate a shift in the weigh-in-motion sensor accurately and also indicate the time point when the system went out of calibration. This methodology can be effectively implemented by state agencies, resulting in more accurate and reliable weigh-in-motion data.     

Reduction of preview distance in lane-keeping control

Lane marker detection is indispensable for a lane-keeping-control algorithm. However, it is impossible to detect lane markers when the curvature of the lane the vehicle is travelling on is large or when there is another car in front of the vehicle with short distance. For lane marker detection, it is desirable to set a preview point close to the vehicle. Therefore, by analyzing the block diagram of driver-vehicle system, we propose a method to reduce preview distance without lane tracking performance deterioration by increasing preview points from the conventional one point to two points. Furthermore, it is revealed that driving along a corner with constant curvature without steady-state deviation and arbitrary design of tracking dynamic characteristics become possible by increasing preview points.