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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.

The utilization of the SLAM (Simultaneous Localization and Mapping) technique was extended from the robotics to the autonomous vehicles for achieving the positioning. However, SLAM cannot obtain the global position of the vehicle but a relative one to the start. For sake of this, a fast and accurate system was proposed to obtain both the local position and the global position of vehicles based on mono-SLAM which realized the SLAM by using monocular camera with a lower cost and power consumption. Firstly, the rough latitude and longitude of current position was obtained by using common GPS without differential signal. Then, the Mono-SLAM operated on the consecutive video frames to generate the localization and local trajectory and its accuracy was further improved by utilizing the IMU information. After that, a piece of Map centered in the rough position obtained by common GPS was downloaded from the Open Street Map.

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.

Being one of the most simple and basic driving scenarios, highway scenario can be one of the first scenarios to achieve autonomous driving. Both car following (CF) and lane changing (LC) are the most basic and frequent maneuver during highway driving tasks, and therefore become two key issues to focus on in recent researches about autonomous vehicle (AV). Different from conventional CF and LC researches that attach much importance to the character, psychology, perception ability, and driving experience of human drivers, more timely and accurate reactions based on fast perception and communication technology as well as the automatic actuator are hypotheses for this research. Moreover, based on these hypotheses, a modified intelligent driver model (MIDM) is proposed for AVs’ following behavior to alleviate the fluctuations caused by lane changing behaviors.

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.

An experimental study is presented on the evaporation of diluted droplet-laden two-phase jet flows within a heated air channel co-flow. In this study, n-heptane is pre-atomized by an ultrasonic nozzle to produce droplet cluster with a median diameter of about15μm, and a continuous cold air flow is applied to carry the fuel droplet cluster to emerge from a nozzle tube, producing a free turbulent jet of droplet stream. The droplet stream is then introduced as a central jet into a square-shaped channel with heated air co-flow for evaporation investigations. With flexibilities of the initial properties of droplet stream and surrounding conditions of channel flow, the axial evolution of droplet size is determined to characterize the evaporation behavior of n-heptane droplet stream under various boundary conditions. The equivalence ratios of droplet streams are varied by changing both the carrier-air flow rate and the fuel flow rate.

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.

The control in transient conditions when hydraulic brake and regenerative brake switch mutually is the key technical issue about electric vehicle hybrid brake system, which has a direct influence on the braking feel of driver and vehicle braking comfort. A coordination control system has been proposed, including brake force distribution correction module and motor force compensation module. Brake force distribution correction module has fixed the distribution results in hydraulic brake force intervention condition, hydraulic brake force evacuation condition and regenerative brake force low speed evacuation condition. Motor compensation module has compensated hydraulic system with motor system, which has fast and accurate response, thus the response of whole hybrid system has been improved.

For achieving vehicle light weighting, the motion deviation is calculated for substitution of PMMA glazing for inorganic glass. In this paper, a test method is proposed to measure and calculate the motion deviation of the dual-curvature glass. To simulate the dual-curvature glass, the torus surface is fitted with least square method according to the window frame data, which are measured by Coordinate Measuring Machine. By using this method, the motion deviation of PMMA glazing and inorganic glass can be calculated, which can not only validate the effectiveness of motion simulation, but also compare the performances. The results demonstrate that the performance of PMMA glazing is better than that of inorganic glass and the simulation results is validated.

In this paper, a new method for determining the forming limit diagram (FLD) of thin sheet metals, called DIC-Grid method, is proposed based on digital image correlation (DIC) technique. It's assumed that there exists one virtual grid with an initial diameter of 2.5mm, which is usually the same dimension as the grid in traditional circular grid analysis, close to the crack of specimen, and the limit strain point on FLD is determined by the deformation of this virtual grid. The DIC-Grid method has been compared with traditional circular grid analysis and the standard ISO/FDIS 12004-2 in Nakajima tests. The results show that the forming limit strains obtained by the newly proposed method are more stable and precise. Furthermore, DIC-Grid method can avoid the measurement error which exists in the circular grid analysis. Meanwhile, it overcomes the shortcomings of time-consuming data processing and non-applicable for unrealistic strain distribution in the method of ISO standard.

The vehicle system is actually a strongly nonlinear system with stochastic parameters. In this paper, the nonlinearities of suspension, tire and seat are analyzed, and the nonlinear dynamics model of driver-vehicle system with 8 degrees of freedom (DOFs) is built. The bifurcation and chaotic motion of the deterministic system under Sinusoid excitations considering the time delay between the front and rear tires are studied. Then, the stochastic feature of the equivalent stiffness and damping coefficients of suspension, tire and seat are assumed to be the normal distribution, and the nonlinear model with random parameters is obtained. The nonlinear dynamics of stochastic nonlinear driver-vehicle system is analyzed and compared through numerical simulation.

This workbook, a companion to the book Road Vehicle Dynamics, 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. Emphasizing application more than theory, the workbook presents systematic rules of analysis that students can follow in a step-by-step manner to understand the efficiencies or shortcomings of various techniques. Readers will gain a greater understanding of the factors influencing ride, handling, braking, acceleration, and vehicle safety.

An adaptive sideslip angle observer based on discrete extended Kalman filter (DEKF) is proposed in this paper and tire-road friction adaptation is also considered. The single track vehicle model with nonlinear tire characteristics is adopted. The tire parameters can be easily obtained through road test data without using special test rig. Afterwards, this model is discretized and the maximum value of tire-road friction is modeled as the third state variable. Through the measurement of vehicle lateral acceleration and yaw rate, the tire-road adhesion coefficient can be timely updated. Simulations with experimental data from road test and driving simulator have confirmed that DEKF has very high accuracy. The convergent speed of DEKF relies on the magnitude of lateral excitation.