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A braking force distribution strategy in integrated braking system composed of the main braking system and the auxiliary braking system based on braking pad wear control and hitch force control under non-emergency braking condition is proposed based on the Electronically Controlled Braking System (EBS) to reduce the difference in braking pad wear between different axles and to decrease hitch force between tractors and trailers. The proposed strategy distributes the braking force based on the desired braking intensity, the degree of the braking pad wear and the limits of certain braking regulations to solve the coupling problems between braking safety, economical efficiency of braking and the comfort of drivers. Computer co-simulations of the proposed strategy are performed.

Taking a good longitudinal braking performance on flat and level road of tractor and semi-trailer combination as a target, in order to achieve an ideal braking force distribution among axles, while the vehicle deceleration is just depend on the driver's intention, not affected by the variation of semi-trailer mass, the paper proposes a model based vehicle mass identification and braking force distribution strategy. The strategy identifies the driver's braking intention via braking pedal, estimates semi-trailer's mass during the building process of braking pressure in brake chamber, distributes braking force among axles by using the estimated mass. And a double closed-loop regulation of the vehicle deceleration and utilization adhesion coefficient of each axle is presented, in order to eliminate the bad effect of mass estimation error, and enhance the robustness of the whole algorithm. A simulation is conducted by utilizing MATLAB/Simulink and TruckSim.

The study of heavy vehicles rollover prediction, especially in algorithm-based heavy vehicles active safety control for improving road handling, is a challenging task for the heavy vehicle industry. Due to the high fatality rate caused by vehicle rollover, how to precisely and effectively predict the rollover of heavy vehicles became a hot topic in both academia and industry. Because of the strong non-linear characteristics of Human-Vehicle-Road interaction and the uncertainty of modeling, the traditional deterministic method cannot predict the rollover hazard of heavy vehicles accurately. To deal with the above issues, this paper applies a probability method of uncertainty to the design of a dynamic rollover prediction algorithm for heavy vehicles and proposes a novel algorithm for predicting the rollover hazard based on the combined empirical model of reliability index and failure probability.

Rollover accident of heavy vehicle during cornering is a serious road safety problem worldwide. In the past decade, based on the active intervention into the heavy vehicle roll dynamics method, researches have proposed effective anti-roll control schemes to guarantee roll stability during cornering. Among those studies, however, roll stability control strategies are generally derived independent of front steering control inputs, the interactive control characteristic between steering and anti-roll system have not been thoroughly investigated. In this paper, a novel roll stability control structure that considers the interaction between steering and anti-roll system, is presented and discussed.

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.

This article presents three assessment approaches of automobile frontal crash pulse by using data from the National Highway Traffic Safety Administration (NHTSA) database (56 km/h frontal crash tests). A direct relationship between structural characteristics and automobile safety is established in the study. In the first approach, the crash pulse criterion is improved in the form of a spider diagram based on the star rating. In the second approach, the crash pulse comprehensive evaluation index (PI) is built by weighting function and correlation analysis between pulse parameters and occupant injury risk indexes. In the final approach, a prediction model for major occupant injury risks and indexes which can be regard as an additional evaluation method of crash pulse quality is built by the multiple linear regression method.

A program of integrated electro-hydraulic braking system is proposed, and its structural composition and working principle are analyzed. According to the structural and mechanical characteristics of all key components, through some reasonable assumptions and simplifications, a motor, a brake master cylinder, four brake wheel cylinders, solenoid valves and an ESP (Electronic Stability Program) algorithm model is set up and simulations of typical braking conditions are carried out based on the Matlab/Simulink. Finally, after the assembly of each sub-model is complete and combining a vehicle which is set up in CarSim software environment, simulation tests and comprehensive performance analysis of the active safety stability control for a vehicle in double lane change and single lane change situations are carried out respectively. According to the dynamic characteristic curves of system, the effects of different structural and control parameters on braking performance are analyzed.

According to the statistics of National Highway Traffic Safety Administration, driver’s cognitive distraction, which is usually caused by drivers using mobile phones, has become one of the main causes of traffic accidents. To solve this problem and guarantee the safety of man-vehicle-road system, the most critical work is to improve the accuracy of driver’s cognitive state detection. In this paper, a novel driver’s cognitive state detecting method based on LightGBM (Light Gradient Boosting Machine) is proposed. Firstly, cognitive distraction experiments of making calls are carried out on a driving simulator to collect vehicle states, eye tracking and EEG (electron encephalogram) data simultaneously and feature extraction is conducted. Then a classifier considering road and individual characteristics used for detecting cognitive states is trained based on LightGBM algorithm, with 3 predefined cognitive states including concentration, ordinary distraction and extreme distraction.

Electronic braking system (EBS) of commercial vehicle is developed based on Anti-lock Braking System (ABS), for the purpose of enhancing the braking performance. Based on the previous study, this paper aims at the development and research on the control strategy of advanced electronic braking system for commercial vehicle, which mainly includes braking force distribution and multiple targets control strategy. In the study of braking force distribution control strategy, the mass of vehicle and the axle loads will be calculated dynamically and the braking force of each wheel will be distributed regarding to the axle loads. The braking intention recognition takes the brake pad wear into account when braking uncritically, so it can detect a difference in the pads between the front and the rear axles. The brake assist strategy supports the driver during emergency braking and the braking distance is shortened by the reduction of the braking system response time.

From the viewpoint of energy conservation and transformation, this paper researches on the braking heat generation and brake temperature change characteristics during heavy-duty tractors brake, and a temperature-predicting model of brake drum is established. According to this model, firstly the entire vehicle kinetic energy is distributed thrice between front and rear axle, tire and road surface friction and sliding friction between hoof and drum, between linings and brake drum, and then the input heat of each drum brakes is figured out through the transformed kinetic energy. Secondly, each brake drum absorbs the heat and results in temperature rise, and dynamics temperature of brake drum is calculated considered cooling due to radiation, conduction, and convection.

A general principle scheme of IEHB (Integrated Electro-Hydraulic Brake system) is proposed, and the working principle of the system is simply introduced in this paper. Considering the structure characteristics of the hydraulic control unit of the system, a kind of time-sharing control strategy is adopted to realize the purpose of independent and precise hydraulic pressure regulation of each wheel brake cylinder in various brake conditions of a vehicle. Because of the strong nonlinear and time varying characteristics of the dynamic brake pressure regulation processes of IEHB, its comprehensive brake performance is mainly affected by temperature, humidity, load change, the structure and control parameters of IEHB, and so on.

Small lightweight electric vehicle (SLEV) is an approach for compensating low energy density of the current battery. However, small lightweight vehicle presents technical challenges to crash safety design. One issue is that mass of battery pack and occupants is a significant portion of vehicle's total weight, and therefore, the mass distribution has great influence on crash response. This paper presents a parametric analysis using finite element modeling. We first build LS-DYNA model of a two-seater SLEV with curb weight of 600 kg. The model has no complex components and can provide reasonable crash pulses under full frontal rigid barrier crash loading and offset deformable barrier (ODB) crash loading. For given mass of battery pack and one occupant (the driver), different battery layouts, representing different combinations of center of gravity and moment of inertia of the whole vehicle, are analyzed for their influences on the crash responses under the two frontal crash loadings.

Lower extremities are the most frequently injured body regions in vehicle-to-pedestrian collisions and such injuries usually lead to long-term loss of health or permanent disability. However, influence of pre-impact posture on the resultant impact response has not been understood well. This study aims to investigate the effects of preimpact pedestrian posture on the loading and the kinematics of the lower extremity when struck laterally by vehicle. THUMS pedestrian model was modified to consider both standing and mid-stance walking postures. Impact simulations were conducted under three severities, including 25, 33 and 40 kph impact for both postures. Global kinematics of pedestrian was studied. Rotation of the knee joint about the three axes was calculated and pelvic translational and rotational motions were analyzed.

Traffic accidents avoidance is one of the main advantages for automated vehicles. As one of the main causes of vehicle collision accidents, lane changing of the ego vehicle in case that the obstacle vehicles appear in the blind spot with uncertain motion intentions is one of the main goals for the automated vehicle. An intention-aware lane changing collision assistance strategy basing on traffic situation assessment in the complex traffic scenarios is proposed in this paper. Typical Regions of Interest (ROI) within the detection range of the blind spots are selected basing on the road topology structures and state space consisting of the ego vehicle and the obstacle vehicles. Then the motion intentions of the obstacle vehicles in ROI are identified basing on Gaussian Mixture Models (GMM) and the corresponding motion trajectories are predicted basing on the state equation.

Diffuse Axonal Injury (DAI) is the most common type of traumatic brain injury, and it is associated with the linear and rotational accelerations resulting from head impacts, which often occurs in traffic related and sports accidents. To investigate the degree of influence of linear and rotational acceleration on DAI, a two-factor, two-level rat head impact experimental protocol involving linear and rotational acceleration was established using the L4(23) orthogonal table in this paper. Following the protocol, rats head was injured and diffusion tensor imaging (DTI) was performed at 24h post-injury to obtain the whole brain DAI injury, and the fractional anisotropy (FA) value of the corpus callosum was selected as the evaluation indicator. Using analysis of variance, the sum of squared deviations for the evaluation indicators was calculated to determine the degree of influence of linear acceleration and rotational acceleration on DAI. The results show that, 1.

The crash safety of lithium-ion batteries has received great attention in recent years because of their growing popularity in electric vehicles. However, the safety issues of prismatic batteries have not been thoroughly studied; in particular, the mechanical responses of prismatic battery cells with lateral constraints under varied loading conditions still remain unclear. In this study, indentation tests are conducted to study the mechanical response of prismatic battery cells. Fixtures providing lateral constraint which simulates the real packing situation in battery module are designed. Firstly, the effects of lateral constraints on coupled mechanical and electrical responses of prismatic battery cells are analyzed and discussed. Secondly, dynamic indentation tests of prismatic cells with lateral constraints are carried out. The response of the stacked batteries under local loading is revealed.

Polyvinyl Butyral (PVB) laminated glass has been widely used in automotive industry as windshield material. Cracks on the PVB laminated glass contain large amount of impact information, which can contribute to accident reconstruction investigation. In this study, the impact-induced in-plane dynamic cracking of the PVB laminated glass is investigated. Firstly, a drop-weight combined with high-speed photography experiment device is set up to investigate the radial cracks propagation on the PVB laminated glass sheet. Both the morphology and the velocity time history curve of the radial cracks are recorded and analyzed to investigate the basic mechanism of the crack propagation process. Afterwards, a three-dimensional laminated plate finite element (FE) model is set up and dynamic cracking process is simulated based on the extended finite element method (XFEM).

In vehicle accident, the bumper beam generally requires high stiffness for sufficient survival space for occupants while it may cause serious pedestrian lower extremity injuries. The aim of this study is to promote an aluminum-steel hybrid material double-hat bumper to meet the comprehensive requirements. The hybrid bumper is designed to improve the frontal crash and pedestrian protection performances in collision accidents. Finite element (FE) models of the hybrid bumper was built, validated, and integrated into an automotive model. The Fixed Deformable Barrier (FDB) and Transport Research Laboratory (TRL) legform model were used to obtain the vehicle crashworthiness and pedestrian lower leg injury indicators. Numerical results showed that the hybrid bumper had a great potential for crashworthiness performance and pedestrian protection characteristics. Based on this, a multi-objective optimization design (MOD) was performed to search the optimal geometric parameters.

It’s hard to achieve complete self-driving using hand-crafting generalized decision-making rules, while the end-to-end self-driving system is low in complexity, does not require hand-crafting rules, and can deal with complex situations. Modular-based self-driving systems require multi-task fusion and high-precision maps, resulting in high system complexity and increased costs. In end-to-end self-driving, we usually only use camera to obtain scene status information, so image processing is very important. Numerous deep learning applications benefit from multi-task learning, as the multi-task learning can accelerate model training and improve accuracy with combine all tasks into one model, which reduces the amount of calculation and allows these systems to run in real-time. Therefore, the approach of obtaining rich scene state information based on multi-task learning is very attractive. In this paper, we propose an approach to multi-task learning for semantics, geometry and motion.

Most of the skin injuries caused by traffic accidents, sports, falls, etc. are in the intermediate strain rate range (1-100s-1), and the injuries may occur at different sites, impact velocities, and orientations. To investigate the multifactorial mechanical properties of rat skin at intermediate strain rates, a three-factor, three-level experimental protocol was established using the standard orthogonal table L9(34), which includes site (upper dorsal, lower dorsal, and ventral side), strain rate (1s-1, 10s-1, and 100 s-1), and sampling orientation (0°, 45°, and 90° relative to the spine). Uniaxial tensile tests were performed on rat skin samples according to the protocol to obtain stress-stretch ratio curves. Failure strain energy was selected as the index, and the influence of each factor on these indexes, the differences between levels of each factor, and the influence of errors on the results were quantified by analysis of variance (ANOVA).