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The driving risk field model offers a feasible approach for assessing driving risks and planning safe trajectory in complex traffic scenarios. However, the conventional risk field fails to account for the vehicle size and acceleration, results in the same trajectories are generated when facing different vehicle types and unable to make safe decisions in emergency situations. Therefore, this paper firstly introduces the acceleration and vehicle size of surrounding vehicles for improving the driving risk model. Then, an integrated decision-making and planning model is proposed based on the combination of the novelty risk field and model predictive control (MPC), in which driving risk and vehicle dynamics constraints are taken into consideration. Finally, the multiple driving scenarios are designed and analyzed for validate the proposed model.

With the development of active safety technology, effort has gradually shifted to preventing or minimizing car crashes. Automatic Emergency Braking Technology (AEB) can avoid accidents by warning and even automatic braking, but there is a contradiction between the accompanying occupant out-of-position and traditional passive safety design. In addition, the 2025 version of C-NCAP plans to add neck injury assessment requirements for AEB [1]. In order to study the kinematic response of the occupant's neck under AEB, a neck finite element model with active muscle force is established in this paper. Firstly, the open-source THOR-50M neck geometric model is used for finite element discretization. Secondly, the neck FE model of THOR-50M is verified through the qualification procedure of the NHTSA standard. Thirdly, according to the geometric features of human neck muscles in Zygote Body database, the neck muscle parameters are preliminarily determined.

Researches on pedestrian protection have become a very important theme in automotive industry. Design for vehicle front-bumper system has proven rather essential and been extensively used to improve the vehicle performance of pedestrian protection. However, there are some limitations in the design of vehicle front-bumper system to meet a multiple-pedestrian impact conditions at the same time. In order to improve the vehicle performance of lower extremity and pelvis protection for pedestrian, a new type of front bumper airbag was developed. Firstly, based on European New Car Assessment Programme (Euro-NCAP), the Flexible Pedestrian Legform Impactor (Flex-PLI) to vehicle and Upper Pedestrian Legform Impactor (U-PLI) to vehicle impact tests are carried out to evaluate the pedestrian protection performance of the initial structure.

Panoramic images can provide critical information for Advanced Driving Assistance Systems (ADAS), such as parking spaces and surrounding vehicles. However, the vehicle in the bird's-eye view image is severely distorted and incomplete, and the visual information becomes very blurred in some illumination insufficient environments. If the driver cannot see the surrounding environment information, the risk of collision will increase, especially during parking. To better percept the local environment with the help of panoramic images, we use panoramic image segmentation results to construct a virtual surround view monitoring system to provide drivers with clearer perception information. Firstly, a lightweight segmentation network is redesigned based on SegNet, which will improve the accuracy of the segmentation without increasing the model’s inference time. Secondly, we build an augment visualization around view monitor (AV-AVM) system with regards to the segmentation results.

The around view monitor (AVM) system for vehicles usually suffers from the distortion of surrounding objects caused by incomplete rectification and stitching, which seriously affects the driver's judgment of the surrounding environment during the reversing process. In response to solve this problem, an augmented around view monitor (AAVM) system fusing image and depth information is proposed, which highlights the point clouds of persons or vehicles at the rear of the vehicle. First, an around view image is generated from four fisheye cameras. Then, the calibration of multi TOF cameras is conducted to improve their accuracy of depth estimation and obtain extrinsic camera positions. Next, the 2D-driven object point cloud detection method is proposed to localize and segment object point clouds like vehicles or persons.

This paper intends to present a novel optimal trajectory planning method for obstacle avoidance on highways. Firstly, a mapping from the road Cartesian coordinate system to the road Frenet-based coordinate system is built, and the path lateral offset in the road Frenet-based coordinate system is represented by a function of quintic polynomial respecting the traveled distance along the road centerline. With different terminal conditions regarding its position, heading and curvature of the endpoint, and together with initial conditions of the starting point, the path planner generates a bunch of candidate paths via solving nonlinear equation sets numerically. A path selecting mechanism is further built which considers a normalized weighted sum of the path length, curvature, consistency with the previous path, as well as the road hazard risk.

The driver's face detection and tracking method important for Advanced Driver Assistance Systems (ADAS) and autonomous driving in various situations. The deep SORT algorithm has integrated appearance information, the motion model and the intersection-over-union (IOU) distance methods, and has been applied to face tracking, but it depends on detection information in every frame. Once the detection information lacks, the deep SORT algorithm will wait until the target detects bounding boxes appear again, even if the target didn’t disappear or shield. Hence, we propose to use a new tracker that not completely depend on the detection algorithm to cascade with the deep SORT algorithm to realize stable driver's face tracking. At first, the driver's face detection and tracking will be accomplished by the MTCNN-deep-SORT algorithm.

Optimization design for vehicle front-end structures has proven rather essential and been extensively used to improve the vehicle performance. Nevertheless, the front-end structure needs to meet the requirement of both pedestrian safety and structural stiffness which are somewhat contradicting to each other. Furthermore, an optimal design could become less meaningful or even unacceptable when some uncertainties present. In the paper, a multi-objective discrete robust optimization (MODRO) algorithm is used to minimize the injury of head and maximize the structural stiffness involving uncertainties. MODRO algorithm is achieved by coupling grey relational analysis (GRA) and principal component analysis (PCA) with Taguchi method. The optimized result shows that the MODRO algorithm improved performance of pedestrian head injury and robustness of the vehicle front-end structure.

This paper presents an optimal cooperative path planning method considering driver’s driving intention for shared control to address target path conflicts during the driver-automation interaction by using the convex optimization technique based on the natural cubic spline. The optimal path criteria (e.g. the optimal curvature, the optimal heading angle) are formulated as quadratic forms using the natural cubic spline, and the initial cooperative path profiles of the cooperative path in the Frenet-based coordinate system are induced by considering the driver’s lane-changing intention recognized by the Support Vector Machine (SVM) method. Then, the optimal cooperative path could be obtained by the convex optimization techniques. The noncooperative game theory is adopted to model the driver-automation interaction in this shared control framework, where the Nash equilibrium solution is derived by the model predictive control (MPC) approach.

Due to the variation of compartment design and occupant’s posture in self-driving cars, there is a new and major challenge for occupant protection. In particular, the studies on occupant restraint systems used in the self-driving car have been significantly delayed compared to the development of the autonomous technologies. In this paper, a numerical study was conducted to investigate the effectiveness of three typical restraint systems on the driver protection in three different scenarios.

An autonomous emergency braking (AEB) system can detect emergency conditions using sensors (e.g., radar and camera) to automatically activate the braking actuator without driver input. However, during the hard braking phase, crash conditions for the restraint system can easily change (e.g., vehicle velocity and occupant position), causing an out-of-position (OOP) phenomenon, especially for unbelted occupants entering the airbag deployment range, which may lead to more severe injuries than in a normal position. A critical step in reducing the injury of unbelted occupants would be to design an AEB system while considering the effect of deployed airbags on the occupants. Thus far, few studies have paid attention to the compatibility between AEB and airbag systems for unbelted occupants. This study aims to provide a method that combines AEB and airbag systems to explore the potential injury reduction capabilities for unbelted occupants.

In order to provide an improved countermeasure for occupant protection, a new type of active reversible preload seatbelt (ARPS) is presented in this paper. The ARPS is capable of protecting occupants by reducing injuries during frontal collisions. ARPS retracts seatbelt webbing by activating an electric motor attached to the seatbelt retractor. FCW (Forward Collision Warning) and LDW (Lane Departure Warning) provide signals as a trigger to activate the electric motor to retract the seatbelt webbing, thus making the occupant restraint system work more effectively in a crash. It also helps reduce occupant’s forward movement during impact process via braking. Four important factors such as preload force, preload velocity and the length and timing of webbing retraction play influential roles in performance of the ARPS. This paper focuses on studying preload performance of ARPS under various test conditions to investigate effects of the aforementioned factors.

The traditional deterministic optimal design is mostly based on meeting regulatory requirements specified in impact standards, without taking the randomness of the impact velocity and angle at the real world situation into consideration. This often leads to the optimization results that converge to the boundary constraints, thus cannot meet the reliability requirements of the product design. Structure members of B-pillar (e.g. inner panel, outer panel, and the reinforcing plate) play a major role in the side impact safety performance. This paper dealt with optimization of B-pillar by considering its dimensions and materials as the design variables, and the impact velocity and angle from real-world traffic accident conditions as the random variable inputs. Using a combination of design of experiment, response surface models, reliability theory and the reliability of design optimization method, a B-pillar was constructed based on the product quality engineering.

The public Hybrid III family finite element models have been used in simulation of automotive safety research widely. The validity of an ATD finite element model is largely dependent on the accuracy of model structure and accurate material property parameters especially for the soft material. For Hybrid III 50th percentile male dummy model, the femur load is a vital parameter for evaluating the injury risks of lower limbs, so the importance of accuracy of knee subcomponent model is obvious. The objective of this work was to evaluate the accuracy of knee subcomponent model and improve the validity of it. Comparisons between knee physical model and knee finite element model were conducted for both structure and property of material. The inaccuracy of structure and the material model of the published model were observed.

The combination of passive and active vehicle safety technologies can effectively improve vehicle safety. Most of them predict vehicle crashes using radar or video, but they can't be applied extensively currently due to the high cost. Another collision forecasting method is more economic which is based on the driver behavior and vehicle status, such as the acceleration, angular velocity of the brake pedal and so on. However, the acceleration and angular velocity of the brake pedal will change with the driver and the vehicle type. In order to study the effect of different drivers and vehicle types on the braking acceleration and angular velocity of the brake pedal, six volunteers were asked to drive five vehicles for simulating the working conditions of emergency braking, normal braking, inching braking and passing barricades under different velocities. All the tests were conducted on asphalt road, and comprehensive experimental design was used to arrange tests.

Lightweight automotive body can be obtained by developing new body constructions, using lightweight materials and structural optimizations, etc. Usually, lighter materials and structural optimizations are main aspects considered in lightweight automotive body engineering. In fact, material costs and manufacturability play more important roles than others in lightweight design. Three lightweight design approaches are considered. The first approach of lightweight design is to replace steels with lighter materials using equal rigidity design method. The second approach is a single objective optimization of mass reduction with materials selection and cost penalty. The third approach is a multi-objective optimization of mass reduction and cost reduction using multi-material concept. These three approaches are applied to an automotive body design problem considering the side impact. Different optimization methods are used to obtain different results.

Air spring due to its superior ride comfort performance has been widely used in distance passenger transporting vehicles. Since the requirements for ride comfort and handling performance are contradict to each other, handling performance and even roll stability are sacrificed to some extent to obtain good ride comfort. Due to the complex terrain and limited manufacturing level, in the past several years, bus rollover accidents with serious casualties have been reported frequently and bus safety has attracted more and more attention from bus manufacturers in China. On one hand the bus standards have to be raised, and on the other hand, novel solutions which can effectively improve the roll stability of air spring bus are needed to replace the inadequacy of anti-roll bars.

Child Restraint Systems (CRS), when used properly, can effectively avoid or reduce injury for children in motor vehicle crashes. To deal with the problems of the high rate of misuse of the CRS and submarining in frontal crashes when child occupants using traditional vehicle seat belts, a novel integrated child safety seat (ICSS) with a four-point seat belt and a ring-shaped lap belt was developed in this study. It is easy to operate and has lower rate of misuse. To study the protection performance of the newly developed ICSS in frontal crashes, a sled test and a series of simulations were conducted. The frontal impact sled test was conducted according to the European regulation ECE R44, which includes a Q6 anthropomorphic test device (ATD) and the impact velocity is 50 km/h. The simulation model included the ICSS model and the Q6 ATD model was developed in the MADYMO software, and the simulation model was validated by the sled test.

As the length of the frontal structure of the minibus can't be as long as cars, some new methods have to be developed to maximum the effect of the energy absorption. In this paper, a step-by-step energy absorption method which based on reverse design was proposed. Two plates with different size and different thickness which can take part in the energy absorption step by step were added in each of the rectangular longitudinal beams. Finite element models were developed both for rectangular beam and minibus. Multi-body model was also developed for the restraint system. The validation of the rectangular beam model was done by sled test, and the minibus model was done by minibus crash test. The computational results matched well with the test results. Then, orthogonal experimental method was used to find the most effective parameters for the energy absorption. These parameters were optimized in the simulation of minibus crash.