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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.

This study aimed to clarify the relationship between truck-pedestrian crash impact velocity and the risks of serious injury and fatality to pedestrians. We used micro and macro truck-pedestrian accident data from the Japanese Institute for Traffic Accident Research and Data Analysis (ITARDA) database. We classified vehicle type into five categories: heavy-duty trucks (gross vehicle weight [GVW] ≥11 × 103 kg [11 tons (t)], medium-duty trucks (5 × 103 kg [5 t] ≤ GVW < 11 × 103 kg [11 t]), light-duty trucks (GVW <5 × 103 kg [5 t]), box vans, and sedans. The fatality risk was ≤5% for light-duty trucks, box vans, and sedans at impact velocities ≤ 30 km/h and for medium-duty trucks at impact velocities ≤20 km/h. The fatality risk was ≤10% for heavy-duty trucks at impact velocities ≤10 km/h. Thus, fatality risk appears strongly associated with vehicle class.

The strength of the passenger compartment is crucial for occupant safety in severe car-to-car frontal offset collisions. Car-to-car crash tests including minicars were carried out, and a low end of crash force was observed in a final stage of impact for cars with large intrusion into the passenger compartment. From overload tests, the strength could be evaluated from collapsing the passenger compartment. Based on the test, the end of crash force as well as the maximum forces might be important criteria to determine the passenger compartment strength, which in turn could predict the large intrusion into the passenger compartment in car-to-car crashes. A 64 km/h ODB test was insufficient to evaluate the potential strength of the passenger compartment because the maximum forces could not be determined in this test.

In side collision accidents, the head is the most frequently injured body region for child occupants seated in a child restraint system (CRS). Accident analyses show that a child's head can move out of the CRS shell, make hard contact with the vehicle interior, and thus sustain serious injuries. In order to improve child head protection in side collisions, it is necessary to understand the injury mechanism of a child in the CRS whose head makes contact with the vehicle interior. In this research, an SUV-to-car oblique side crash test was conducted to reconstruct such head contacts. A Q3s child dummy was seated in a CRS in the rear seat of the target car. The Q3s child dummy's head moved out beyond the CRS side wing, moved laterally, and made contact with the side window glass and the doorsill. It was demonstrated that the hard head contact, which produced a high HIC value, could occur in side collisions.

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.

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).

The number of traffic deaths in Japan was 4,914 in 2009. Since the head was the most common site of injury in traffic accidents (2,302, 47%), traumatic brain injury causes the fatalities in these accidents. The aim of the present study was to quantify micro injuries in the animal brain for gaining insight and understanding of the human brain injury tolerance. Using porcine brain matter, in vitro stress relaxation experiments and in vivo impact experiments were conducted. In both experiments, the distribution of the damage ratio of the transverse to longitudinal length of cells, hereafter, referred to as an aspect ratio, in the brain matter under loading was examined. In the in vitro stress relaxation experiments, specimens were compressed vertically with a compression velocity of 1 mm/s, and the displacement was held for 140 sec when the compression strain reached the target strain. In the experiments, there were five categories of compression strain: 10, 20, 30, 40, and 50 percent.

The number of traffic deaths in Japan was 4,863 in 2010. Pedestrians account for the highest number (1,714, 35%), and vehicle occupants the second highest (1,602, 33%). Pedestrian protection is a key countermeasure to reduce casualties in traffic accidents. A striking vehicle's impact velocity could be considered a parameter influencing the severity of injury and possibility of death in pedestrian crashes. A collision damage mitigation braking system (CDMBS) using a sensor to detect pedestrians could be effective for reducing the vehicle/pedestrian impact velocity. Currently in Japan, cars equipped with the CDMBS also have vision sensors such as a stereo camera for pedestrian detection. However, the ability of vision sensors in production cars to properly detect pedestrians has not yet been established. The effect of reducing impact velocity on the pedestrian injury risk has also not been determined.

As a new brake-by-wire solution, the electro-booster (Ebooster) brake system can work with the electronic stability program (ESP) equipped in the real vehicle to realize various excellent functions such as basic force boosting (BFB), active braking and energy recovery, which is promoting the development of smart vehicles. Among them, the BFB is the function of Ebooster's servo force to assist the driver's brake pedal force establishing high-intensity braking pressure. After the BFB function failure of the Ebooster, it was not possible to provide sufficient brake pressure for the driver's normal braking, and eventually led to traffic accidents. In this paper, a compensation redundancy control strategy based on ESP is proposed for the BFB failure of the self-designed Ebooster.

With the rapid development of science and technology, the automobile industry is developing rapidly, and intelligent networking and autonomous driving have become new research hotspots. The safety and efficiency of vehicle driving has always been an important research topic in the transportation field. Due to reducing the participation of drivers, autonomous vehicles can reduce traffic accidents caused by human factors. While the development of intelligent networking can achieve information sharing between vehicles, and improve driving efficiency to a certain extent. Based on the game theory and the minimum safe distance condition, this paper establishes a lane changing decision model of intelligent network-connected autonomous vehicles, puts forward a game payoff function and analyzes the game strategy.

The high popularity of automobiles has led to frequent collisions. According to the latest statistics of the United Nations, about 1.25 million people worldwide die from road traffic accidents each year. In order to improve the safety of vehicles in driving, the active safety system has become a research hotspot of various car companies and research institutions around the world. Among them, the more mature and popular active security system are Forward Collision Warning(FCW) and Autonomous Emergency Braking(AEB). However, the current active safety system is based on traditional sensors such as radar and camera. Therefore, the system itself has many limitations due to the shortage of traditional sensors. Compared to traditional sensors, Vehicle to Everything (V2X) technology has the advantages of richer vehicle parameter information, no perceived blind spots, dynamic prediction of dangerous vehicle status, and no occlusion restriction.

This study aims to clarify the relation between axonal deformation and the onset of axonal injury. Firstly, to examine the influence of strain rate on the threshold for axonal injury, cultured neurons were subjected to 12 types of stretching (strains were 0.10, 0.15, and 0.20 and strain rates were 10, 30, 50, and 70 s-1). The formation of axonal swellings and bulbs increased significantly at strain rates of 50 and 30 s-1 with strains of 0.15 and 0.20, respectively, even though those formations did not depend on strain rates in cultures exposed to a strain of 0.10. Then, to examine the influence of the strain along an axon on axonal injury, swellings were measured at every axonal angle in the stretching direction. The axons that were parallel to stretching direction were injured the most. Finally, we proposed an experimental model that subjected an axon to more accurate strain.

The hippocampus plays a crucial role in brain function and is one of the important areas of concern in closed head injury. Hippocampal injury is related to a variety of factors including the strength of mechanical load, animal age, and helmet material. To investigate the order of these factors on hippocampal injury, a three-factor, three-level experimental protocol was established using the L9(34) orthogonal table. A closed head injury experiment regarding impact strength (0.3MPa, 0.5MPa, 0.7MPa), rat age (eight- week-old, ten-week-old, twelve-week-old), and helmet material (steel, plastic, rubber) were achieved by striking the rat's head with a pneumatic-driven impactor. The number of hippocampal CA3 cells was used as an evaluation indicator. The contribution of factors to the indicators and the confidence level were obtained by analysis of variance.

Acute repetitive traumatic brain injury (rTBI) can occur in a pedestrian collision when the head hits the vehicle and the ground twice, as well as in a serial rear-ended collision in a very short period. This study established an animal model of acute rTBI to investigate the cumulative effects of repetitive brain injury under different combinations of impact levels. 117 adult male Sprague–Dawley (SD) rats (190±20g) were divided into control, single impact, and repeated impact groups, with the single impact group was divided into three subgroups of mild, moderate, and severe. And the repeated impact group was divided into nine subgroups by combining mild, moderate, and severe. The kinematic response parameters of the rat’s head were captured by a high-speed camera and acceleration sensors. Modified neurological severity score (mNSS) was performed at 6h after final injury, and the severity of injury was quantified using the abbreviated injury scale (AIS).

Chest injuries occur frequently in frontal collisions. During impact, tension in the lap belt is transferred to the inboard shoulder belt, which compresses the lower ribs of the occupant. In this research, inboard shoulder belt and lap belt geometries and forces were investigated to reduce chest deflection. First, the inboard shoulder belt geometry was changed by the lap/shoulder belt (L/S) junction for the rear seat occupant in sled tests using Hybrid III finite element simulation, sled tests and THOR simulation. As the L/S junction was closer to the ASIS (anterior superior iliac spine), chest deflection of the Hybrid III was smaller. The L/S junction around the ilium has the potential to reduce chest deflection without significant increase of head excursion. For THOR, although the chest deflection reduction effect due to closer L/S junction to the ASIS was observed, chest deflection was still substantially large since the lap belt overrode the ASIS.