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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.

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.

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.

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.

Good handling stability becomes very important for heavily-laden electric wheel dump trucks that are operated on rough roads. To improve handling stability of mining dump trucks, nonlinear stiffness and nonlinear damping of the hydro-pneumatic suspension were considered as optimization variables. In this paper, based on the Daubechies wavelet's compactness and regularization and least-square method, the nonlinear stiffness and damping are identified. In order to verify the results of the parameter identification, the multi-body system dynamic model of the truck was built in ADAMS/view. By comparing the simulated results and tested ones, we find acceleration-history and power spectral density of acceleration are very close. And then, based on the approximate model method, the optimization model was built in ISIGHT. The nitrogen column and the orifice diameter were defined as the design variables. Finally, the handling stability was optimized by applying the genetic algorithms method.