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The research and development of data-driven highly automated driving system components such as trajectory prediction, motion planning, driving test scenario generation, and safety validation all require large amounts of naturalistic vehicle trajectory data. Therefore, a variety of data collection methods have emerged to meet the growing demand. Among these, camera-equipped drones are gaining more and more attention because of their obvious advantages. Specifically, compared to others, drones have a wider field of bird's eye view, which is less likely to be blocked, and they could collect more complete and natural vehicle trajectory data. Besides, they are not easily observed by traffic participants and ensure that the human driver behavior data collected is realistic and natural. In this paper, we present a complete vehicle trajectory data extraction framework based on aerial videos. It consists of three parts: 1) objects detection, 2) data association, and 3) data cleaning.

A dynamic controller is designed for unmanned skid-steering vehicle. The vehicle speed is controlled through driving torque of engine to achieve the desired vehicle speed and the steering is controlled through hydraulic braking on each side of the vehicle to achieve the desired yaw rate. Contrary to the common approaches by considering non-holonomic constraints, tire slip and saturation of actuators torque influencing the driving and braking are considered, based on the analysis of vehicle dynamic model and nonlinear tire model. Hence, with conditional integrators, the dynamic controller overcoming integral saturation is designed to ensure the accurate tracking for desired signals under influence of tire forces and constraint of actuators. In addition, the exponential kind filter is utilized to enhance the ability of smoothing noise of wheel speed. To perform small radius cornering maneuvers, a dynamic control strategy for steering when vehicle speed is zero is also designed.

A rapid path-planning algorithm that generates drivable paths for an autonomous vehicle operating in structural road is proposed in this paper. Cubic B-spline curve is adopted to generating smooth path for continuous curvature and, more, parametric basic points of the spline is adjusted to controlling the curvature extremum for kinematic constraints on vehicle. Other than previous approaches such as inverse kinematics, model-based prediction postprocess approach or closed-loop forward simulation, using the kinematics model in each iteration of path for smoothing and controlling curvature leading to time consumption increasing, our method characterized the vehicle curvature constraint by the minimum length of segment line, which synchronously realized constraint and smooth for generating path. And Differ from the path of robot escaping from a maze, the intelligent vehicle traveling on road in structured environments needs to meet the traffic rules.

BBW (Brake-by-wire) can increase the electric and hybrid vehicles performance and safety. This paper proposes a novel mechatronic booster system, which includes APS (active power source), PFE (pedal feel emulator), ECU (electronic control unit). The system is easily disturbed when the system parameters and the outside conditions change. The system performance is weakened. The cascade control technique can be used to solve the problem. This paper develops an adaptive cascade optimum control (ACOC) algorithm based on the novel mechatronic booster system. The system is divided into main loop and servo loop, both of them are closed-loop system. The servo-loop system can eliminate the disturbance which exists in the servo loop. So the robustness of the cascade control system is improved than which of the general closed-loop control system. Different control object is respectively chosen. The control-oriented mathematical model is designed.

Based on the four-wheel-drive electric vehicle (4WD EV), a variable structure control (VSC) strategy is designed in this paper for the anti-lock braking control. With nonpeak friction coefficient as target, sign judgment method of switch function in this VSC strategy is improved and a new control algorithm is proposed. The improved VSC strategy is made robust to the parameters of the algorithm and verified by the computer simulation as well as the hard-in-loop test. The results show that the slip rate can be controlled to a point in the stable area near the optimal slip ratio and the control strategy can effectively realize the anti-lock braking control.

Harmony-with-traffic refers to the ability of autonomous vehicles to maximize the driving benefits such as comfort, efficiency, and energy consumption of themselves and the surrounding traffic during interactive driving under traffic rules. In the test of harmony-with-traffic, one or more background vehicles that can respond to the driving behavior of the vehicle under test are required. For this purpose, the functional requirements of car-following model for harmony-with-traffic evaluation are analyzed from the dimensions of test conditions, constraints, steady state and dynamic response. Based on them, an interactive car-following model (ICFM) is developed. In this model, the concept of equivalent distance is proposed to transfer lateral influence to longitudinal. The calculation methods of expected speed are designed according to the different car-following modes divided by interaction object, reaction distance and equivalent distance.

BBW (Brake-by-wire) can increase the vehicle safety performance due to high control accuracy and fast response speed. As one solution of BBW, the novel Integrated-electro-hydraulic brake system (I-EHB) is proposed, which consists of electro-hydraulic booster and hydraulic pressure control unit. The electro-hydraulic booster is activated by an electric motor that driving linear motion mechanism to directly produce the master cylinder pressure. With electro-hydraulic booster as an actuator, the hydraulic pressure control problem is a key issue. Most literatures deal with the pressure control issue based on the feedback pressure signal measured by pressure sensor. As far as the authors are aware, none of the proposed techniques takes into account the pressure sensor unequipped BBW. In this paper, there is no pressure feedback signal, but there is only position feedback signal measured by position sensor for control law design.

With the electrification and intelligentialization of vehicle, requirements on more intelligent and integrated brake system are put forward. A novel integrated-electro-hydraulic brake system (I-EHB) for automotive is presented to fulfill these requirements. I-EHB is consisted of active power source (APS), pedal feel emulator (PFE), electro control unit (ECU) and hydraulic control unit (HCU). The system characteristics of I-EHB are tested through test rig. According to characteristics experiments, friction and non-linear phenomena in hydraulic pressure control are found. In order to overcome these phenomena in control of I-EHB, chatter-compensation is adopted based on experiment analysis. Algorithm are tested and optimized through test rig. As a result, through chatter-compensation the hydraulic pressure is controlled accurately and chatter-compensation is optimized for different working conditions.

For an electric vehicle driven by four in-wheel motors, the torque of each wheel can be controlled precisely and independently. A closed-loop control method of differential drive assisted steering (DDAS) has been proposed to improve vehicle steering properties based on those advantages. With consideration of acceleration requirement, a three dimensional characteristic curve that indicates the relation between torque and angle of the steering wheel at different vehicle speeds was designed as a basis of the control system. In order to deal with the saturation of motor's output torque under certain conditions, an anti-windup PI control algorithm was designed. Simulations and vehicle tests, including pivot steering test, lemniscate test and central steering test were carried out to verify the performance of the DDAS in steering portability and road feeling.

With the development of autonomous driving, the penetration rate of autonomous vehicles on the road will continue to grow. As a result, the social cooperation ability of autonomous vehicles will have a great effect on the social acceptance of autonomous driving, which can be described as harmony with traffic. In order to research the evaluation method of the harmony with traffic, this paper proposes a subjective and objective mapping evaluation method based on the Mean Impact Value and Backpropagation (MIV-BP) Neural Network, with the merging vehicle on the expressway ramp as the research object. Firstly, by taking 16 original objective indexes obtained by theoretical analysis and the subjective evaluation results as input and output, respectively, the BP Neural Network model is constructed as a baseline model. Secondly, nine selected objective indexes are selected by the MIV method based on the baseline model.

In this paper, an integrated electronic hydraulic brake(I-EHB) system is introduced, which is mainly composed of a motor, a worm gear, a worm, a gear, a rack etc. The friction leads the system to the creeping phenomenon and the dead zone. These phenomenon seriously affect the response speed and the hydraulic pressure control .In order to realize the accurate hydraulic pressure control of I-EHB system, a new friction compensation control method is proposed based on LuGre dynamic friction model. And the theoretical design of adaptive control method is designed based on the feedback of the master cylinder pressure and the operating state of the system. Then the stability of the control method is proved by Lyapunov theorem. A co-simulation model is built with Matlab/Simulink and AMESim, so as to prove the validity of the control method.

In this paper, the initial disc thickness variation (DTV) of a ventilated disc in automotive brake system is modeled as sinusoidal function of the second order. The transient thermomechanical coupling properties of the brake system is simulated using finite element (FE) modeling. The system models and results were verified by a thermomechanical coupling test of a disc brake conducted on a brake dynamometer. By using varied evaluation indexes such as the temperature distribution, the normal stress and the elastic deformation of disc surfaces, the influences of the initial DTV and its direction as well as its amplitude on the thermomechanical coupling characteristics were analyzed.

The transient thermo-mechanical coupling dynamic model of ventilated disc brake with asymmetrical outer and inner thickness was established by means of Msc-marc software. In the model, pad backplate is simplified as a rigid surface with the same shape of brake lining and is bonded together with brake lining. Control node is associated with the rigid surface and the equivalent force that replaces the pressure is applied on the control nodes, of which the degrees of freedom in radial and rotational directions are constrained. With distribution characteristics of disc temperature field, normal stress field and lateral thermo-elastic deformation and thickness for the evaluation, the impacts of brake pad constraints on brake thermomechanical coupling characteristics were analyzed. The simulation results show that the brake pad back plate is an important structure in brake thermo-mechanical coupling analysis, which can’t be ignored in simulation computing.

This paper describes a methodology to estimate longitudinal velocity of a 4-wheel-drive electric vehicle, in which wheel driven torque can be independently controlled by electric motor. Without non-driven wheels it would be difficult to estimate the vehicle longitudinal velocity precisely, especially when all of four wheels have large slip ratio. Therefore, an estimation methodology based on fuzzy logic is put forward, which uses four wheel speed and longitudinal acceleration as input signals. However, this method works not very well when two or more wheels have large slip ratio. In order to improve estimation effect, a state variable filter is designed to calculate wheel acceleration signals, which are used as additional signals to the fuzzy logic observer. Furthermore, the possibility of using four wheel driving torque signals to improve the estimation precision is also discussed.

This paper describes a methodology to estimate yaw rate of a 4-wheel-drive electric vehicle, in which wheel driven torque can be independently controlled by electric motor. Without non-driven wheels it would be difficult to estimate the vehicle yaw rate precisely, especially when some of the four wheels have large slip ratio. Therefore, a model based estimation methodology is put forward, which uses four wheel speeds, steering wheel angle and vehicle lateral acceleration as input signals. Firstly the yaw rate is estimated through three different ways considering both vehicle kinematics and vehicle dynamics. Vehicle kinematics based method has good estimation accuracy even when the vehicle has large lateral acceleration. However, it can not provide satisfying results when the wheel has large slip ratio. In contrast, vehicle dynamics based method is not so sensitive to wheel slip ratio.

On the dual-motor electric vehicle, which is driven by two electric motors mounted on the front and rear axles respectively, longitudinal dynamic control and electro-dynamic braking can be achieved by controlling the torque of front and rear axle motors respectively. Suspension displacement is related to the wheel torque, thus the pitch of vehicle body can be influenced by changing the torque distribution ratio. The pitch of the body has a great influence on the vehicle comfort, which occurs mainly during acceleration and braking progress. Traditionally active suspension is adopted to control the pitch of body. Instead, in this paper an ideal torque distribution strategy is developed to limit the pitch during acceleration and braking progress. This paper first explores the relationship between the torque distribution and the body pitch through the real vehicle test, which reveals the feasibility of the vehicle comfort promotion by optimizing the torque distribution coefficient.

Automotive radar is the most important component in the autonomous driving system, which detects the obstacles, vehicles and pedestrians around with acceptable cost. The target tracking is one of the key functions in the automotive radar which estimates the position and speed of the targets having regarding to the measurement inaccuracy and interferences. Modern automotive radar requires a multi-target tracking algorithm, as in the radar field of view hundreds of targets can present. In practice, the automotive radar faces very complicated and fast-changing road conditions, for example tunnels and curved roads. The targets’ unpredictable movements and the reflections of the electromagnetic wave from the tunnel walls and the roads will make the multi-target tracking a difficult task. Such situation may last several seconds so that the continuous tracks of the targets cannot be maintained and the tracks are dropped mistakenly.

In this paper we present a path following control design for a six-wheel skid-steering vehicle. Contrary to the common approaches that impose non-holonomic constraints, a dynamic vehicle model is established based on a pseudo-static tire model, which uses tire slip to determine tire forces. Our control system admits a modular structure, where a motion controller computes the reference vehicle yaw rate and reference vehicle speed and a dynamics controller tracks these signals. A robust nonlinear control law is designed to track the reference wheel speeds determined by the dynamics controller with proved stability properties. Saturated control techniques are employed in designing the reference yaw rate, which ensures the magnitude of the reference yaw rate does not violate the constraint from the ground-tire adhesion. The simulation results demonstrate the effectiveness of the proposed path following control design.

This paper presents several pressure estimation algorithms (PEAs) for a decoupled electro-hydraulic brake system (EHB), which is driven by an electric motor + reduction gear. Most of the pressure control solutions are based on standard pressure-based feedback control, requiring a pressure signal. Although the pressure sensor can produce the pressure feedback signal, it will increase cost and enlarge installation space. The rotation angle of electric motor is available by the built-in sensor, so the pressure can be estimated by using the rotation angle. Considering the typical nonlinearities (i.e. friction, pressure-position relationship) and uncertainties (i.e. disturbance caused by friction model), the estimation-oriented model is established. The LuGre model is selected to describe the friction, and the pressure-position relationship is fitted by a quadratic polynomial.

To research the dynamic response of active power source of electronic hydraulic brake system, the paper proposes a restricted distribution control strategy. Building control strategy model and active power source model to simulation with Matlab/Simulink and AMEsim, and bench test is conducted on different driving cycles, which proves that the dynamic response of active power source is fit and controllable by adjusting PID parameters.