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Taking full advantage of available traffic environment information, making control decisions, and then planning trajectory systematically under structured roads conditions is a critical part of intelligent vehicle. In this article, a lane-changing decision-making method for intelligent vehicle is proposed based on acceleration field. Firstly, an acceleration field related to relative velocity and relative distance was built based on the analysis of braking process, and acceleration was taken as an indicator of safety evaluation. Then, a lane-changing decision method was set up with acceleration field while considering driver’s habits, traffic efficiency and safety. Furthermore, velocity regulation was also introduced in the lane-changing decision method to make it more flexible.

Road test simulation on test rig is widely used in the automobile industry to shorten the development circles. However, there is still room for further improving the time cost of current road simulation test. This paper described a new method considering both the damage error and the runtime of the test on a multi-axial test rig. First, the fatigue editing technique is applied to cut the small load in road data to reduce the runtime initially. The edited road load data could be reproduced on a multi-axial test rig successfully. Second, the rainflow matrices of strains on different proving ground roads are established and transformed into damage matrices based on the S-N curve and Miner rules using a reduction method. A standard simulation test for vehicle reliability procedure is established according to the proving ground schedule as a target to be accelerated.

Lane detection is one of the most important part in ADAS because various modules (i.e., LKAS, LDWS, etc.) need robust and precise lane position for ego vehicle and traffic participants localization to plan an optimal routine or make proper driving decisions. While most of the lane detection approaches heavily depend on tedious pre-processing and great amount of assumptions to get reasonable result, the robustness and efficiency are deteriorated. To address this problem, a novel framework is proposed in this paper to realize robust and real-time lane detection. This framework consists of two branches, where canny edge detection and Progressive Probabilistic Hough Transform (PPHT) are introduced in the first branch for efficient detection.

Effectively detecting road boundaries in real time is critical to the applications of autonomous vehicles, such as vehicle localization, path planning and environmental understanding. To precisely extract the road boundaries from the 3D-LiDAR data, a dedicated algorithm consisting of four steps is proposed in this paper. The steps are as follows: Firstly, the 3D-LiDAR data is pre-processed by employing the RANSAC method, the ground points are quickly separated from the original 3D-LiDAR point cloud to reduce the disturbance from the obstacles on the road, this greatly decreases the size of the point cloud to be processed. Secondly, based on the principle of 3D-LiDAR scanning, the ground points are divided into scan layers. And the road boundary points of each scan layer are detected by using three spatial features based on sliding window.

Autonomous driving technology is more and more important nowadays, it has been changing the living style of our society. As for autonomous driving planning and control, vehicle dynamics has strong nonlinearity and uncertainty, so vehicle dynamics and control is one of the most challenging parts. At present, many kinds of specific vehicle dynamics models have been proposed, this review attempts to give an overview of the state of the art of vehicle dynamics models for autonomous driving. Firstly, this review starts from the simple geometric model, vehicle kinematics model, dynamic bicycle model, double-track vehicle model and multi degree of freedom (DOF) dynamics model, and discusses the specific use of these classical models for autonomous driving state estimation, trajectory prediction, motion planning, motion control and so on.

This paper has designed a real time control algorithm to use ISG motor actively compensate the torque ripple produced by the engine, to reduce torsional vibration. This paper consists of 3 parts. In the first section, this paper has introduced the research object and its modification for experiments. Then the development of control strategy is presented. The engine dynamic model is built, and real-time control with a feedforward unit and a feedback unit is derived. Encoder and cylinder pressure is used for engine torque estimator. Then the ISG motor output the counter-waveform to make the overall output smooth. In order to verify the effectiveness of the control strategy, the final section has established a test bench, where two experiments are carried out. One of the experimental conditions is to set the engine at a constant operating point, while the other is to crank the engine from 0 rpm to idle speed with ISG motor.

The vehicle pull problem is very important to driving safety. Major factors that may cause the pull problem related to tire include variations of geometric dimension (e.g. RPK) and stiffness (e.g. cornering stiffness, aligning stiffness), plysteer and conicity. In previous research, the influencing mechanism of these factors was well studied. But in fact, vehicle pull problem caused by tire is probabilistic. When we assemble four tires onto the car, there could be 384 different assembly arrangements. If there are significant differences among these four tires, there will also be significant differences in the influence of different tire assembly schemes on vehicle pull, which has not been systematically discussed in previous studies. If we want to evaluate the pull performance of all these arrangements by vehicle test, it will be a time consuming process which will take almost 24 working days, along with a high test expense.

Automated parking is an efficient way to solve parking difficulties and path planning is of great concern for parking maneuvers [1]. Meanwhile, the starting region of path planning greatly affects the parking process and efficiency. The present research of the starting region are mostly determined based on a single algorithm, which limits the flexibility and efficiency of planning feasible paths. This paper, taking parallel parking and vertical parking for example, proposes a method to calculate the starting region and select the most suitable path planning algorithm for parking, which can improve the parking efficiency and reduce the complexity. The collision situations of each path planning algorithm are analyzed under collision-free conditions based on parallel and vertical parking. The starting region for each algorithm can then be calculated under collision-free conditions.

Studying traffic accidents by using naturalistic driving data has become increasingly appealing for its potential benefits in improving road safety. This paper presents findings from a field test which has been conducted on 50 taxis in the urban areas of Beijing for 10 months using Video Drive Recorders (VDRs). The VDR used in this study could record the information of vehicle front view video, vehicle states, as well as driver operations immediately before and after an event. The drivers were given no specific instructions during the test, and the instrumentation for data collection was unobtrusive. Important safety-relevant parameters, such as vehicle speed, pre-event maneuver, time headway, time-to-collision, and driver reaction time, were calculated with precision. Based on these parameters, an analysis into features and causes of rear-end conflicts is performed.

The performance parameters of torsional vibration damper, including stiffness and damping, have great influence on the torsional vibration of automobile driveline. At present, the research on torsional vibration damper mainly concentrates on the torsional stiffness, but rarely on the torsional damping characteristics. This paper systematically studied the effect of torsional stiffness and damping on torsional vibration of automobile driveline under uniform speed conditions, accelerated and decelerated conditions, idling conditions and resonance conditions. The requirements on stiffness and damping of various operating conditions were summarized. The effect and requirements researched were useful to performance match design of torsional vibration damper.

With the progressing autonomy of driving technology, machine is assuming greater responsibility for driving tasks to enhance safety. Leveraging this potential, this paper introduces a novel human-machine co-steering control strategy based on model predictive control. The strategy is designed to address the difficulties faced by drivers when driving on surfaces with low adhesion. Firstly, the proposed strategy utilizes a parallel human-machine co-steering framework with a weight allocation concept between the controller and the driver. Moreover, the nonlinear controller dynamics model and linear driver dynamics model are developed to characterize the interaction behaviors between human and machine under low-adhesion road surface conditions. And a nonlinear game optimization problem is formulated to capture the cooperative interaction relationship between human and machine.

Clarifying accident causations can provide a strong foundation to prevent traffic accidents and reduce severities. This paper uses Chinese government census data from 1996-2003[1∼8] and models a relationship between various kinds of traffic accident causations and the severities of the traffic accidents based on neural network combined (NNC). The paper adapts multi-folder cross validation concept to enhance the properties of NNC. It then conducts sensitivity analysis on the trained NNC to identify the prioritized importance of traffic accident causations as they are to the severities of traffic accident. Lastly, the results are validated and compared by the findings of previous researches.

With the development of cellular communication technology and for the sake of reducing drag resistance, the multi-lane platoon technology will be more prosperous in the future. In this article, the cooperative vehicle platoon method on the public road is represented. The method’s architecture is mainly composed of the following parts: decision-making, path planning and control command generation. The decision-making uses the finite state machine to make decision and judgment on the cooperative lane change of vehicles, and starts to execute the lane change step when the lane change requirements are met. In terms of path planning, with the goal of ensuring comfort, the continuity of the vehicle state and no collision between vehicles, a fifth-order polynomial is used to fit every vehicle trajectory. In terms of control command generation module, a model predictive control algorithm is used to solve the multi-vehicle centralized optimization control problem.

With the rapid development of intelligent driving technology, there has been a growing interest in the driving comfort of automated vehicles. As vehicles become more automated, the role of the driver shifts from actively engaging in driving tasks to that of a passenger. Consequently, the study of the passenger experience in automated driving vehicles has emerged as a significant research area. In order to examine the impact of automatic driving on passengers' riding experience in vehicle platooning scenarios, this study conducted real vehicle experiments involving six participants. The study assessed the subjective perception scores, eye movement, and electrocardiogram (ECG) signals of passengers seated in the front passenger seat under various vehicle speeds, distances, and driving modes. The results of the statistical analysis indicate that vehicle speed has the most substantial influence on passenger perception.

Recent research has shown that butanol, instead of ethanol, has the potential of introducing a more suitable blend in diesel engines. This is because butanol has properties similar to current transportation fuels in comparison to ethanol. However, the main downside is the high cost of the butanol production process. Acetone-butanol-ethanol (ABE) is an intermediate product of the fermentation process of butanol production. By eliminating the separation and purification processes, using ABE directly in diesel blends has the potential of greatly decreasing the overall cost for fuel production. This could lead to a vast commercial use of ABE-diesel blends on the market. Much research has been done in the past five years concerning spray and combustion processes of both neat ABE and ABE-diesel mixtures. Additionally, different compositions of ABE mixtures had been characterized with a similar experimental approach.

In this research, propane flash boiling sprays discharged from a five-hole gasoline direct injector were studied in a constant volume vessel. The fuel temperature (Tfuel) ranged from 30 °C to 90 °C, and the ambient pressure (Pamb) varied from 0.05 bar to 11.0 bar. Different flash boiling spray behavior compared to that under sub-atmospheric conditions was found at high Pamb. Specifically, at the sub-atmospheric pressures, the individual flashing jets merged into one single jet due to the strong spray collapse. In contrast, at Pamb above 3.0 bar and Tfuel above 50 °C, the spray collapse was mitigated and the flashing jets were separated from each other. Further analyses revealed that the mitigation of spray collapse at high Pamb was ascribed to the suppression of jet expansion. In addition, it was found that the spray structure was much different at similar Rp, indicating that Rp lacked the generality in describing the structure of flash boiling sprays.

The wireless inter-vehicle communication provide a manner to achieve multi-vehicle cooperative driving, and the platoon of automotive vehicle can significantly improve traffic efficiency and ensure traffic safety. Previous researches mostly focus on the state of the proceeding vehicle, and transmit information from self to the succeeding vehicle. Nevertheless, this structure possesses high requirements for controller design and shows poor effect in system stability. In this paper, the state of vehicles is not only related to the information of neighbor vehicles, while V2V communication transmit information over a wide range of area. To begin with, the node dynamic model of vehicle is described by linear integrator with inertia delay and the space control strategy is proposed with different topological communication structures as BF, LBF, PBF, etc.

Traffic congestions are increasingly severe in urban areas, especially at the merging areas of the ramps and the arterial roads. Because of the complex conflict relationship of the vehicles in ramps and arterial roads in terms of time-spatial constraints, it is challenging to coordinate the motion of these vehicles, which may easily cause congestions at the merging areas. The connected and automated vehicles (CAVs) provides potential opportunities to solve this problem. A centralized merging control method for CAVs is proposed in this paper, which can organize the traffic movements in merging areas efficiently and safely. In this method, the merging control model is built to formulate the vehicle coordination problem in merging areas, which is then transformed to the discrete nonlinear optimization form. A simulation model is built to verify the proposed method.

This paper presents a new magnetorheological braking which can be used in vehicles. Magneto-rheological (MR) fluid is a novel material which can be used in different components of vehicle. Magneto-rheological fluids (MRF) are suspensions of micron size whose yield stress varies rapidly as the change of magnetic field. The use of MRF in vehicles has been gaining popular recently due to its strong rheological effect, fast response and low energy consumption. Besides, these performances give designers more choice in automotive designs. However, most of the related research of MRF brake is about the construction of small prototype to verify its rheological performance. As a result, research progress is limited to calculation and simulation which make the braking force of prototype can hardly meet the requirement of vehicle due to a lack of optimal design and the understanding of MRF in the situation of high sheer stress and magnetic field.

In this paper, it was researched the degradation characteristics of catalytic performance of three kinds of DPFs (C1, C2 and C3, with precious metal concentrations being 15, 25 and 35 g/ft3 respectively) after diesel truck aging. It is found out that the crystallinity of three kinds of DPF samples (Used) in full vehicle aging was higher than that of fresh samples (Fresh) and aged samples (Aged) in the laboratory. Compared with Fresh samples, the concentration of Pt atom in precious metal on the surface of Aged and Used samples tends to decrease in most cases. Activities to CO and C3H8 of Aged and Used samples of three kinds of DPFs had all been degraded, and activity degradation showed a substantial correlation with concentration reduction rate of precious metal on the carrier surface. NO2 productivity of Used samples all rose. Crystallinity of DPF samples after full vehicle aging in Inlet, Middle and Outlet areas successively increased.