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The radar-based advanced driver assistance systems (ADAS) like autonomous emergency braking (AEB) and forward collision warning (FCW) can reduce accidents, so as to make vehicles, drivers and pedestrians safer. For active safety, automotive millimeter-wave radar is an indispensable role in the automotive environmental sensing system since it can work effectively regardless of the bad weather while the camera fails. One crucial task of the automotive radar is to detect and distinguish some objects close to each other precisely with the increasingly complex of the road condition. Nowadays almost all the automotive radar products work in bidimensional area where just the range and azimuth can be measured. However, sometimes in their field of view it is not easy for them to differentiate some objects, like the car, the manhole covers and the guide board, when they align with each other in vertical direction.

Multi-Target tracking is a central aspect of modeling the surrounding environment of autonomous vehicles. Automotive millimeter-wave radar is a necessary component in the autonomous driving system. One of the biggest advantages of radar is it measures the velocity directly. Another big advantage is that the radar is less influenced by environmental conditions. It can work day and night, in rainy or snowy conditions. In the expressway scenario, the forward-looking radar can generate multiple objects, to properly track the leading vehicle or neighbor-lane vehicle, a multi-target tracking algorithm is required. How to associate the track and the measurement or data association is an important question in a multi-target tracking system. This paper applies the nearest-neighbor method to solve the data association problem and uses an extended Kalman filter to update the state of the track.

Battery models are often applied to describe the dynamic characteristics of batteries and can be used to predict the state of the battery. Due to the process of charging and discharging, the battery heat generation will cause the inhomogeneity between inner battery temperature and surface temperature. In this paper, a novel battery impedance model, which takes the impact of the battery internal temperature gradient on battery impedance into account, is proposed to improve the battery model performance. Several experiments are designed and conducted for pouch typed battery to investigate the electrochemical impedance spectroscopy (EIS) characteristics with the artificial temperature gradient (using a heating plate). Experimental results indicate that the battery internal temperature gradient will influence battery EIS regularly.

Positioning system is a key module of autonomous driving. As for LiDAR SLAM system, it faces great challenges in scenarios where there are repetitive and sparse features. Without loop closure or measurements from other sensors, odometry match errors or accumulated errors cannot be corrected. This paper proposes a construction method of LiDAR anchor constraints to improve the robustness of the SLAM system in the above challenging environment. We propose a robust anchor extraction method that adaptively extracts suitable cylindrical anchors in the environment, such as tree trunks, light poles, etc. Skewed tree trunks are detected by feature differences between laser lines. Boundary points on cylinders are removed to avoid misleading. After the appropriate anchors are detected, a factor graph-based anchor constraint construction method is designed. Where direct scans are made to anchor, direct constraints are constructed.

Automated driving system is a multi-source sensor data fusion system. However different type sensor has different operating frequencies, different field of view, different detection capabilities and different sensor data transition delay. Aiming at these problems, this paper introduces the processing mechanism of out of sequence measurement data into the multi-target detection and tracking system based on millimeter wave radar and camera. After the comparison of ablation experiments, the longitudinal and lateral tracking performance of the fusion system is improved in different distance ranges.

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.

As the connectivity of vehicles increases rapidly, more vehicles have the capability to communicate with each other. Because Vehicular Ad-hoc NETworks (VANETs) have the characteristics of solid mobility and decentralization, traditional security strategies such as authentication, firewall, and access control are difficult to play an influential role. As a soft security method, trust management can ensure the security attributes of VANETs. However, the rapid growth of newly encountered nodes of the trust management system also increases the requirements for trust establishing mechanisms. Without a proper trust establishment mechanism, the trust value of the newly encountered nodes will deviate significantly from its actual performance, and the trust management system will suffer from newcomer attacks.

Image corruptions due to noise, blur, contrast change, etc., could lead to a significant performance decline of Deep Neural Networks (DNN), which poses a potential threat to DNN-based autonomous vehicles. Previous works attempted to explain corruption from a Fourier perspective. By comparing the absolute Fourier spectrum difference between corrupted images and clean images in the RGB color space, they regard the noise from some corruptions (Gaussian noise, defocus blur, etc.) as concentrating on the high-frequency components while others (contrast, fog, etc.) concentrate on the low-frequency components. In this work, we present a new perspective that unifies corruptions as noise from high frequency and thus propose an image augmentation algorithm to achieve a more robust performance against common corruptions. First, we notice the 1/fα statistical rule of the natural image's spectrum and the channels-wise differential sensitivity on the YCbCr color space of the Human Visual System.

Lane Keeping Assistance System (LKAS) is a typical lateral driver assistance system with low acceptance. One of the main reasons is that fixed parameters cannot satisfy individual differences. So LKAS adaptive to driver characteristics needs to be designed. Driver Steering Override (DSO) process is an important process of LKAS. It happens when contradiction between driver’s intention and system behavior occurs. As feeling of overriding will affect the overall experience of using LKAS, the design of DSO characteristics is worthy of attention. This research provided an adaptive design scheme aiming at DSO characteristics for LKAS by building Driver Preference Model (DPM) based on simulator test data from preliminary experiments. The DPM was to represent the relationship between driver characteristics indices and driver preferred system characteristics indices. So that new drivers’ preference can be predicted by DPM based on their own daily driving data with LKAS switched off.

Electric Power Steering (EPS) is the actuator of several lateral-dynamic-related Advanced Driver Assistance Systems (ADAS). A driving simulator with EPS will be much helpful for the ADAS development. However, if a real EPS is used in the driving simulator, it is quite difficult to realize the road reaction force accurately and responsively. To overcome this weakness, a virtual EPS platform is established. The virtual EPS platform contains two parts: one is the vehicle and EPS model, the other is the force feedback actuator (FFA) of the Steer-by-Wire (SBW) system. The FFA is an interface between the driver and the EPS/vehicle model. The reactive torque of the FFA is obtained based on the models. Meanwhile, the input of the EPS model is the steering angle of the FFA. Comparing to a real EPS, the virtual EPS platform has a problem of instability because of the actuator lag of the FFA. Therefore, a damping control method is applied to make the system stable.

As a key parameter of fundamental electrical, mutual inductance always used to characterize the overall performance of wireless power transfer (WPT) system in electric vehicle charging applications. However, in real case, factors such as parking misalignments, load variations and intrusion of foreign objects would result in a variation of mutual inductance between both coils, which may adversely impact on transmitted power and transmission efficiency. Therefore, in this paper, we propose to identify mutual inductance parameter with the least square method (LSM) based on the equivalent circuit model. In section II, COMSOL is adopted to simulate mutual inductance variation with the change of lateral offset. In section III, the differential equation is derived from the state space equation of the WPT system. Through identifying the process parameters, the mutual inductance of coils can be obtained by the functional relationship between them.

Automatic Lane Change (ALC) function is an important step to promote the currently popular Advanced Driver Assistance Systems (ADAS) within a single lane. The key issue for ALC is accurate steering angle and trajectory tracking during the lane changing process. In this paper, an MPC controller with a receding horizon is designed to track the desired trajectory. During the tracking process, other objectives such as safety and smoothness are considered. Considering of the practical mechanism and parameter uncertainties, an SMC controller is designed to track the target steering angle. For validation, a Hardware-in-the-Loop (HIL) experiment platform is established, and experiments of different control algorithms under different conditions are carried out successively. Comparisons of the experiment results of MPC+SMC and PID+SMC schemes indicate that both the trajectory error and the steering angle error of the former combination are smaller.

Radar is playing more and important role in multiple object detection and tracking system due to the fact that Radar can not only determine the velocity instantly but also it is less influenced by environment conditions. However, Radar faces the problem that it has many detection clutter，false alarms and detection results are easily affected by the reflected echoes of road boundary in traffic scenes. Besides this, With the increase of the number of targets and the number of effective echoes, the number of interconnection matrices increases exponentially in joint probability data association, which will seriously affect the real-time and accuracy of high-speed scene algorithms.in the tracking system. So, A method of using millimeter wave radar to detect and fit the boundary guardrail of high-speed road is proposed, and the fitting results are applied to the vehicle detection and tracking system to improve the tracking accuracy.

Lane-keeping assist system (LKA) alerts the driver or intervenes in the driving when the vehicle deviates from the lane. But its effect is highly dependent on the driver’s acceptance. Distance to Lane Crossing (DTLC) and Time to Lane Crossing (TTLC) are two important factors to consider the danger level of the scenario, which are also two references for drivers to make decisions. At present, most of the functional design standards are based on these values, while they often differ for different vehicle movements. This study uses a driving robot to precisely control the test conditions and performs field tests on two advanced autonomous vehicles in National Intelligent Connected Vehicle (Shanghai) Pilot Zone. The test conditions are extended based on various test standards and the LKA performance of vehicles in the pre-experiment.

Driver behaviors provide abundant information and feedback for future Advanced Driver Assistance Systems (ADAS). Driver’s eye and head may present some typical movement patterns before executing driving maneuvers. It is possible to use driver’s head and eye movement information for predicting driver intention. Therefore, to determine the most important features related to driver intention has attracted widespread research interests. In this paper, a method to analyze the correlation between driver’s visual features and driver intention is proposed, aiming to determine the most representative features for driver intention prediction. Firstly, naturalistic driving experiment is conducted to collect driver’s videos during executing lane keeping and lane change maneuvers. Then, driver’s head and face visual features are extracted from those videos. By using boxplot and independent samples T-test, features which have significant correlation with driver intention are found.

By means of particle image velocimetry(PIV) measurements, this paper uses vortex identification algorithms to find and analyze the coherent structures in the shear layer region of a 1:15 scaled 3/4 open jet automotive wind tunnel with a high Reynolds number(about 106), referring to SAWTC’s AAWT. The proper orthogonal decomposition(POD) is used to process the PIV experimental data to reconstruct the velocity fields. Based on the vortex identification functions, the locations of the center, the rotation direction and the radius of vortex can be computed. Furthermore, this paper uses the statistical method to study the regularities of distribution of these vortexes in a two-dimensional plane, and identify the vortex pairing process in the shear layer region. This paper also chooses different vortex identification algorithms to find the most accurate and suitable algorithms.

LiDAR and camera fusion have emerged as a promising approach for improving place recognition in robotics and autonomous vehicles. However, most existing approaches often treat sensors separately, overlooking the potential benefits of correlation between them. In this paper, we propose a Cross- Modality Module (CMM) to leverage the potential correlation of LiDAR and camera features for place recognition. Besides, to fully exploit potential of each modality, we propose a Local-Global Fusion Module to supplement global coarse-grained features with local fine-grained features. The experiment results on public datasets demonstrate that our approach effectively improves the average recall by 2.3%, reaching 98.7%, compared with simply stacking of LiDAR and camera.

To overcome some drawbacks of using UHSS (Ultra High Strength Steel) in vehicle weight reduction, like spot weld HAZ (Heat Affected Zone) softening, hard machining and brittleness, a new solution of ultra-high stress strengthening was proposed and applied to the ridgelines of thin-walled structures in this paper. Firstly, stress distribution characteristics, the laws of stress variation and the compressed plate buckling process of the rectangular thin-walled beam under compressive and bending load were analyzed in elastic plastic stage by theory and Finite Element (FE) simulation. Secondly, based on elastic plastic buckling theory of the compressed plate and stress distribution similarity of the buckling process of the thin-walled box structure, three factors influencing the ultimate resistance enhancement of thin-walled hat section beam were found, and the rationality and accuracy of cross section ultimate resistance prediction formulas were also verified by FE simulation.

Carbon fiber reinforced plastic (CFRP) composites have gained particular interests due to their high specific modulus, high strength, lightweight and resistance to environment. In the automotive industry, numerous studies have been ongoing to replace the metal components with CFRP for the purpose of weight saving. One of the significant benefits of CFRP laminates is the ability of tailoring fiber orientation and ply thickness to meet the acceptable level of structural performance with little waste of material capability. This study focused on the concurrent optimization of ply orientation and thickness for CFRP laminated engine hood, which was based on the gradient-based discrete material and thickness optimization (DMTO) method. Two manufactural constraints, namely contiguity and intermediate void constraints, were taken into account in the optimization problem to reduce the potential risk of cracking matrix of CFRP.

Beamforming techniques are widely used today in aeroacoustic wind tunnels to identify wind noise sources generated by interaction between incoming flow and the test object. In this study, a planar spiral microphone array with 120 channels was set out-of-flow at 1:1 aeroacoustic wind tunnel of Shanghai Automotive Wind Tunnel Center (SAWTC) to test exterior wind noise sources of a production car. Simultaneously, 2 reference microphones were set in vehicle interior to record potential sound source signal near the left side view mirror triangle and the signal of driver’s ear position synchronously. In addition, a spherical array with 48 channels was set inside the vehicle to identify interior noise sources synchronously as well. With different correlation methods and an advanced algorithm CLEAN-SC, the ranking of contributions of vehicle exterior wind noise sources to interested interior noise locations was accomplished.