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The WorldSID dummy can be equipped with both a pubic and a sacroiliac joint (S-I joint) loadcell. Although a pubic force criterion and the associated injury risk curve are currently available and used in regulation (ECE95, FMVSS214), as of today injury mechanisms, injury criteria, and injury assessment reference values are not available for the sacroiliac joint itself. The aim of this study was to investigate the sacroiliac joint injury mechanism. Three configurations were identified from full-scale car crashes conducted with the WorldSID 50th percentile male where the force passing through the pubis in all three tests was approximately 1500 N while the sacroiliac Fy / Mx peak values were 4500 N / 50 Nm, 2400 N / 130 Nm, and 5300 N / 150 Nm, respectively. These tests were reproduced using a 150 kg guided probe impacting Post Mortem Human Subjects (PMHS) at 8 m/s, 5.4 m/s and 7.5 m/s.

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

Many efforts have been made to understand the mechanism of whiplash injury. Recently, the cervical facet joint capsules have been focused on as a potential site of injury. An experimental approach has been taken to analyze the vertebral motion and to estimate joint capsule stretch that was thought to be a potential cause of pain. The purpose of this study is to analyze the kinematics of the cervical facet joint using a human FE model in order to better understand the injury mechanism. The Total Human Model for Safety (THUMS) was used to visually analyze the local and global kinematics of the spine. Soft tissues in the neck were newly modeled and introduced into THUMS for estimating the loading level in rear impacts. The model was first validated against human test data in the literature by comparing vertebrae motion as well as head and neck responses. Joint capsule strain was estimated from a maximum principal strain output from the elements representing the capsule tissues.

This paper analyzed the mechanisms of injury in high speed, right-lateral impacts of stock car auto racing, and interaction of the occupant and the seat system for the purpose of reducing the risk of injury, primarily rib fractures. Many safety improvements have been made to stock car racing recently, including the Head and Neck Support devices (HANS®), the 6-point restraint harnesses, and the implementation of the SAFER Barrier. These improvements have contributed greatly to mitigating injury during the race crash event. However, there is still potential to improve the seat structure and the understanding of the interaction between the driver and the seat in the continuation of making racing safety improvements. This is particularly true in the case of right-lateral impacts where the primary interaction is between the seat supports and the driver and where the chest is the primary region of injury.

Posterior translation of the tibia with respect to the femur can stretch the posterior cruciate ligament (PCL). Fifteen millimeters of relative displacement between the femur and tibia is known as the Injury Assessment Reference Value (IARV) for the PCL injury. Since the anterior protuberance of the tibial plateau can be the first site of contact when the knee is flexed, the knee bolster is generally designed with an inclined surface so as not to directly load the projection in frontal crashes. It should be noted, however, that the initial flexion angle of the occupant knee can vary among individuals and the knee flexion angle can change due to the occupant motion. The behavior of the tibial protuberance related to the knee flexion angle has not been described yet. The instantaneous angle of the knee joint at the timing of restraining the knee should be known to manage the geometry and functions of knee restraint devices.

A feasible method was developed to reconstruct the three-dimensional flame surface of SI combustion based on 2D images. A double-window constant volume vessel was designed to simultaneously obtain the side and bottom images of the flame. The flame front was reconstructed based on 2D images with a slicing model, in which the flame characteristics were derived by slicing flame contour modeling and flame-piston collision area analysis. The flame irregularity and anisotropy were also analyzed. Two different principles were used to build the slicing model, the ellipse hypothesis modeling and deep learning modeling, in which the ellipse hypothesis modeling was applied to reconstruct the flame in the optical SI engine. And the reconstruction results were analyzed and discussed. The reconstruction results show that part of the wrinkled and folded structure of the flame front in SI engines can be revealed based on the bottom view image.

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.

Traffic accidents in the United States were analyzed using FARS and NASS data. When classified according to vehicle body type and collision type, fatalities were most common in the case of (1) passenger car to passenger car frontal impacts, (2) passenger car to passenger car side impacts, (3) passenger car to LTV side impacts, (4) passenger car to truck frontal impacts, and (5) passenger car to LTV frontal impacts. Among these collisions, it was clearly confirmed that the occupants of a passenger car have a strong tendency to suffer injury when “the passenger car has a frontal impact with a heavier passenger car,” “the passenger car has a frontal impact with an LTV/SUV, truck,” and “the passenger car is side impacted by an LTV/SUV,” or the like. These examples should be recognized as clear cases of incompatibility. This paper will describe an approach which aim at improving compatibility. However, around 60% of occupants who suffer fatal injuries are not wearing a seat belt.

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.

Approximately 20% of traffic fatalities in United States 2012 were caused by rollover accidents. Mostly injured parts were head, chest, backbone and arms. In order to clarify the injury mechanism of rollover accidents, kinematics of six kinds of Anthropomorphic Test Devices (ATD) and Post Mortem Human Subjects (PMHS) in the rolling compartment, whose body size is 50th percentile male (AM50), were researched by Zhang et al.(2014) using rollover buck testing system. It was clarified from the research that flexibility of the backbone and thoracic vertebra affected to occupant’s kinematics. On the other hand, the kinematics research of body size except AM50 will be needed in order to decrease traffic fatalities. There were few reports about the researches of occupant kinematics using FE models of body sizes except AM50.

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state).

It is known that the collisions caused by lane departure events account for range of percentages among the countries studied. To help prevent such collisions, the Lane Departure Warning (LDW) system has started to be introduced in production vehicles, but there is little research on its benefits and limitations so far. In this paper we performed an in-depth analysis of the collisions and driver-related essential variables for the lane-departure collision scenarios and demonstrated the benefit estimation process. The benefit of the LDW system is estimated by comparing lane departure events when the vehicle has no LDW, and how they change with the addition of LDW. The event without LDW was modeled in 5 phases: (1) before departure, (2) starting of the departure, (3) departed the lane, (4) at the impact with an object, and, (5) after the impact. “An extensive analysis was conducted of traffic crash data compiled by the Institute for Traffic Accident Research and Data Analysis (ITARDA).

Vehicle Stability Control (VSC) is a system designed to help drivers when skidding or unstable vehicle behavior is about to occur. We have studied the characteristics of VSC in reducing accidents by analyzing accident data statistics in Japan. The results indicate that VSC is effective in reducing single car accidents and head-on collisions with other automobiles. In these accidents, the analysis showed that VSC may be more helpful in reducing a larger number of accidents in the higher speed range where vehicle dynamics plays a greater part. It also showed that VSC may contribute to reducing accidents that result from unstable vehicle behavior. VSC demonstrated more effectiveness in reducing accidents involving lateral & rear impacts than those of frontal impacts, and in reducing accidents on wet & snowy/icy roads than those on dry roads.

Teammate Advanced Drive is a driving support system with state-of-the-art automated driving technology that has been developed for customers’ safe and secure driving on highways based on the Toyota’s Mobility Teammate Concept. This SAE Level 2 (L2) system assists overtaking, lane changes, and branching to the destination, in addition to providing hands-free lane centering and car following. The automated driving technology includes self-localization onto a High Definition Map, multi-modal sensing to cover 360 degrees of the surrounding environment using fusion of LiDARs, cameras, and radars, and a redundant architecture to realize fail-safe operation when a malfunction or system limitation occurs. High-performance computing is provided to implement deep learning for predicting and responding to various situations that may be encountered while driving.

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.

Due to the relative high speed and short distance between the door and occupant, side impact presents a challenging task when analyzing the input force from the door to the occupant. The new FMVSS214 Final Rule in 2007 and the new NCAP in 2008 mandated the use of a SID-IIs in the oblique pole impact test and in the rear seat during an MDB side impact test. Therefore, a high-precision measurement and calculation of the three-dimensional dummy kinematics, as well as the interaction of force inside the dummy (internal force) and force exerted from outside the dummy (external force) will help provide efficient evaluation of design requirements for the door trim and supplemental restraint systems that meet legally mandated requirements.

Collisions between opened doors and approaching vehicles such as bicycles are common occurrences in urban areas around the world. For example, in Chicago, 20% of all bicycle accidents involve collisions with doors, which occur over 300 times a year. In addition, there are concerns about a further rise in accidents due to the recent increase in home delivery services and bicycle commuting during the COVID-19 pandemic. Some advanced driver assistance systems (ADAS) that are designed to help prevent this type of accident have already been introduced. These systems detect approaching vehicles with sensors and alert the person opening the door via LED lights or a buzzer when the door is opened. The occupant must understand the meaning of the alert and stop opening the door quickly to prevent an accident. However, if the occupant is an elderly person or a child, it is difficult to stop opening the door quickly.

According to the U.S. National Highway Traffic Safety Administration, 743 pedal cyclists were killed and 48,000 were injured in motor vehicle crashes in 2013. As a novel active safety equipment to mitigate bicyclist crashes, bicyclist Pre-Collision Systems (PCSs) are being developed by many vehicle manufacturers. Therefore, developing equipment for evaluating bicyclist PCS is essential. This paper describes the development of a bicycle carrier for carrying the surrogate bicyclist in bicyclist PCS testing. An analysis on the United States national crash databases and videos from TASI 110 car naturalistic driving database was conducted to determine a set of most common crash scenarios, the motion speed and profile of bicycles. The bicycle carrier was designed to carry or pull the surrogate bicyclist for bicycle PCS evaluation. The carrier is a platform with a 4 wheel differential driving system.

In recent years, GPFs (Gasoline particulate filters) have been installed in gasoline engines to comply with stricter environmental regulations in China and Europe. In particular, coated-GPFs having a catalytic purification function are required to have high conversion performances, high filter efficiencies in the sense of a high collection efficiency, and low pressure loss. It is not easy to design a filter that satisfies all these parameters. Experimental studies are being conducted, but it is costly to study in trial productions. In this technical paper, a GPF design optimization method will be proposed that combines multi-scale simulation, surrogate models by machine learning, and an optimization algorithm. By using this method, a GPF design that minimizes pressure loss while providing high conversion performance and particle collection rates that satisfy current regulations can be created.

The goal of this study was to develop injury probability functions for the leg bending moment and MCL (Medial Collateral Ligament) elongation of the Flexible Pedestrian Legform Impactor (Flex-PLI) based on human response data available from the literature. Data for the leg bending moment at fracture in dynamic 3-point bending were geometrically scaled to an average male using the standard lengths obtained from the anthropometric study, based on which the dimensions of the Flex-PLI were determined. Both male and female data were included since there was no statistically significant difference in bone material property. Since the data included both right censored and uncensored data, the Weibull Survival Model was used to develop a human leg fracture probability function.