Search Results

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 safe driver program has been established through a public-private partnership. This program targets novice drivers and uses a combination of classroom and in-vehicle training exercises to address critical driver errors known to lead to crashes. Students participate in four modules: braking to learn proper stopping technique, obstacle avoidance / reaction time to facilitate proper lane selection and collision avoidance, tailgating to learn about following distances, and loss of control to react appropriately when a vehicle is about to become laterally unstable. Knowledge pre and posttests are also administered at the start and end of the program. Students' in-vehicle driving performance are evaluated by instructors as well as recorded by onboard data acquisition units. The data has been evaluated with objective and subjective grading rubrics. The 70 participants in three classes used as a case study achieved an average skill score of 83.93/100.

Testing any new safety technology of Autonomous Vehicles (AV) and Advanced Driver Assistance Systems (ADAS) requires simulation-based validation and verification. The specific scenarios used for testing, outline incidences of accidents or near-miss events. In order to simulate these scenarios, specific values for all the above parameters are required including the ego vehicle model. The ‘criticality’ of a scenario is defined in terms of the difficulty level of the safety maneuver. A scenario could be over-critical, critical, or under-critical. In over-critical scenarios, it is impossible to avoid a crash whereas, for under-critical scenarios, no action may be required to avoid a crash. The criticality of the scenario depends on various parameters e.g. speeds, distances, road/tire parameters, etc. In this paper, we propose a definition of criticality metric and identify the parameters such that a scenario becomes critical.

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.

Understanding the effects of tire and vehicle properties on the rollover propensity of tractor semi-trailer trucks is essential. The major objective of the project described by this paper was to develop a simplified computational tool that can be used to understand and predict the effects of various tire characteristics and truck design parameters on rollover under steady cornering and non-tripped conditions. In particular, this tool may be used to help understand the basic mechanisms governing rollover propensity of trucks equipped with New Generation Wide Single tires as contrasted with conventional tires. Effects of tire flexibility, roll-compliant suspensions, fifth - wheel lash and nonlinear suspension characteristics are included in the model and are presented below. Design parameter data used as input to the model were obtained from Michelin Americas Research and Development Corporation.

Understanding the parameters which influence the tendency for a heavy truck to exhibit rollover is of paramount importance to the trucking industry. Multiple parameters influence the vehicle’s motion, and the ability to determine how each affects the vehicle as a system would be an indispensable tool for the design of such vehicles. To be able to perform such predictions and analysis, models and a computer simulation were created to allow the examination of changes in design parameters in such vehicles. The vehicle model was originally developed by Law [1] and presented in Law and Janajreh [2]. The model was extended further by Lawson [3, 4] to include (a) the effects of the torsional compliance of both the tractor and trailer, and (b) tanker trailers with various levels of liquid fill. In the present paper, both the tractor and trailer compliances were studied independently to determine their influences on the rollover stability of the vehicle.

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.

Current military operations in Iraq and Afghanistan are unique because the battlefield can be described as a non-linear, asymmetrical environment. Units operate in zones that are susceptible to enemy contact from any direction at any time. The response to these issues has been the addition of add-on armor to HMMWV's and other tactical vehicles. The retro-fitting of armor to these vehicles has resulted in many accidents due to rollover and instability. The goal of this paper is to determine possible causes of the instability and rollover of up-armored tactical vehicles and to develop simulation tools that can analyze the steady-state and transient dynamics of the vehicles. Models and simulations include a steady-state rollover scenario, analysis of understeer gradient, and a transient handling analysis that uses models of both a human driver and a vehicle to analyze vehicle response to an obstacle avoidance maneuver.

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).

Multibody human models are widely used to investigate responses of human during an automotive crash. This study aimed to validate a commercially available multibody human body model against response corridors from volunteer tests conducted by Naval BioDynamics Laboratory (NBDL). The neck model consisted of seven vertebral bodies, and two adjacent bodies were connected by three orthogonal linear springs and dampers and three orthogonal rotational springs and dampers. The stiffness and damping characteristics were scaled up or down to improve the biofidelity of the neck model against NBDL volunteer test data because those characteristics were encrypted due to confidentiality. First, sensitivity analysis was performed to find influential scaling factors among the entire set using a design of experiment.

Occupant restraint systems are developed based on some baseline experiments. While these experiments can only represent small part of various accident modes, the current procedure for utilizing the restraint systems may not provide the optimum protection in the majority of accident modes. This study presents an approach to predict occupant injury responses before the collision happens, so that the occupant restraint system, equipped with a motorized pretensioner, can be adjusted to the optimal parameters aiming at the imminent vehicle-to-vehicle frontal crash. The approach in this study takes advantage of the information from pre-crash systems, such as the time to collision, the relative velocity, the frontal overlap, the size of the vehicle in the front and so on. In this paper, the vehicle containing these pre-crash features will be referred to as ego vehicle. The information acquired and the basic crash test results can be integrated to predict a simplified crash pulse.