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Torque Vectoring Control for distributed drive electric vehicle is studied. A handling improvement algorithm for normal cornering maneuvers is proposed based on state variable feedback control: Yaw rate feedback together with steer angle feedforward is employed to improve transient response and steady gain of the yaw rate, respectively. According to the feedback coefficient's influence on the transient response, an optimization function is proposed to obtain optimum feedback coefficients under different speeds. After maximum feedforward coefficients under different speeds are obtained from the constraint of the motor exterior characteristic, final feedforward coefficients are calculated according to an optimal steering characteristic. A torque distribution algorithm is presented to help the driver to speed up during the direct yaw moment control.

Vehicle and pedestrian detection technology is the most important part of advanced driving assistance system (ADAS) and automatic driving. The fusion of millimeter wave radar and camera is an important trend to enhance the environmental perception performance. In this paper, we propose a method of vehicle and pedestrian detection based on millimeter wave radar and camera. Moreover, the proposed method complete the detection of vehicle and pedestrian based on dynamic region generated by the radar data and sliding window. First, the radar target information is mapped to the image by means of coordinate transformation. Then by analyzing the scene, we obtain the sliding windows. Next, the sliding windows are detected by HOG features and SVM classifier in a rough detect. Then using the match function to confirm the target. Finally detecting the windows in a precision detection and merging the detecting windows. The target detection process is carried out in the following three steps.

The undesired shifting phenomenon(USP) occurs easily under the braking or climbing conditions etc., and its impact is the discomfort to the passengers or cause of vehicle's state contrary to the driver's intention, meanwhile, the wear of the clutch and synchronizer is increased, so their lifetime are greatly shortened. To the vehicle with dual clutch transmission (DCT), undesired shifting phenomenon will lead to frequent and unnecessary actuation of synchronizer for the use of pre-engagement synchronizer in the shifting control; therefore, its occurrence should be eliminated as far as possible. In this paper, the process of the undesired shifting of the vehicle with DCT is elaborated, then the generating cause of USP is described based on directed graph.

Automatic lane change of intelligent vehicles is a complex process. Besides of safety, feelings of the driver and passengers during the lane change are also very important. In this paper, a lane change trajectory planner is designed to generate an ideal collision-free trajectory to satisfy the driver’s preference. Various lane changing modes, gentle lane change, general lane change, radical lane change and personalized lane change, are designed to meet the needs of different passengers on vehicles simultaneously. In this paper, the condition of the two-lane change is studied. One vehicle is in front of the ego vehicle at the same lane and one is at the rear of the ego vehicle at the target lane. A trajectory planning method is then established based on constant speed offset and sine curve, vehicle distances and speed difference, etc. The key factors which can reflect drivers’ lane change characteristics are then acquired.

Millimeter wave automotive radar is one of the most important sensors in the Advanced Driver Assistance System (ADAS) and autonomous driving system, which detects the target vehicles around the ego vehicle via processing transmitted and echo signals. However, the sampling rate of classical radar signal processing methods based on Nyquist sampling theorem is too high and the resolution of range, velocity and azimuth can’t meet the requirement of highly autonomous driving, especially azimuth. In spatial domain, targets are sparse distribution in the detection range of automotive radar. To solve these problems, the algorithm for targets location based on compressed sensing for automotive radar is proposed in this paper. Besides, the feasibility of the algorithm is verified through the simulation experiments of traffic scene. The range-doppler-azimuth model can be used to estimate the distance, velocity and azimuth of the target accurately.

Target detection is essential to the advanced driving assistance system (ADAS) and automatic driving. And the data fusion of millimeter wave radar and camera could provide more accurate and complete information of targets and enhance the environmental perception performance. In this paper, a method of vehicle and pedestrian detection based on the data fusion of millimeter wave radar and camera is proposed to improve the target distance estimation accuracy. The first step is the targets data acquisition. A deep learning model called Single Shot MultiBox Detector (SSD) is utilized for targets detection in consecutive video frames captured by camera and further optimized for high real-time performance and accuracy. Secondly, the coordinate system of camera and radar are unified by coordinate transformation matrix. Then, the parallel Kalman filter is used to track the targets detected by radar and camera respectively.

Automotive radar is an important environment perception sensor for advance driving assistance system. It can detect objects around the vehicle with high accuracy and it works in all bad weathers. For traditional automotive radar, it cannot measure the objects’ height. Thus, a manhole cover on the road surface or a guideboard high above the road would be taken erroneously as a non-moving car. In such cases, the adaptive cruise system would decelerate or stop the vehicle erroneously and make the driver uncomfortable. A 3D automotive radar with two-dimensional electronic scanning can measure the targets’ height as well as the targets’ azimuth angle. This paper presents a 79 GHz ultra-wide band automotive 3D imaging radar. Due to the 4 GHz wide bandwidth, the range resolution of this radar can be as small as 3.75 cm.

In this paper, by analyzing multiple electro-hydraulic brake system schemes in detail, the idea of dual-motor electro-hydraulic brake system is proposed. As a new solution, the dual-motor electro-hydraulic brake system can actively simulate pedal feel, make the most of pedal power (from the driver), and reduce the maximum power output of each active power source remarkably, which is a distinctive innovation compared to most current electro-hydraulic brake systems. Following the proposed concept, a general research thought and method is conceived, and then a dual-motor electro-hydraulic brake system is designed. Finally, the simulation model is set up in AMESim software and its feasibility is simulated and verified.

This set combines the book Road Vehicle Dynamics with its corresponding workbook companion, Road Vehicle Dynamics: Problems and Solutions. Road Vehicle Dynamics provides a detailed overview of the dynamics of road vehicle systems, giving readers an understanding of how physical laws, human factor considerations, and design choices affect ride, handling, braking, acceleration, and vehicle safety. Chapters cover analysis of dynamic systems, tire dynamics, ride dynamics, vehicle rollover analysis, handling dynamics, braking, acceleration, total vehicle dynamics, and accident reconstruction. The workbook will enable students and professionals from a variety of disciplines to engage in problem-solving exercises based on the material covered in each chapter of that book. It presents systematic rules of analysis that students can follow in a step-by-step manner to understand the efficiencies or shortcomings of various techniques.