Search Results

The National Highway Safety Administration (NHTSA) is collecting crash data relating to large trucks. Two data collection programs are specified. One is a crash causation study to investigate the cause of fatal and serious large truck crashes over two years. The other study is a continuous effort collecting data on large truck motor carrier crashes in each state, as coded on police accident reports.

This paper describes ongoing research conducted by the National Highway Traffic Safety Administration (NHTSA) to evaluate the potential of safety restraints on large school buses. School bus transportation is one of the safest forms of transportation in the United States. Large school buses provide protection because of their visibility, size, and weight, as compared to other types of motor vehicles. Additionally, they are required to meet minimum Federal Motor Vehicle Safety Standards (FMVSS) mandating compartmentalized seating, emergency exits, roof crush and fuel system integrity, and minimum bus body joint strength.

Pedestrian research and testing at the NHTSA Vehicle Research and Test Center has recently focused on assessment of proposed ISO and EEVC head impact test procedures, and extension of these procedures to additional vehicle frontal surfaces. In addition to test parameter sensitivity evaluation, reconstruction of PCDS (Pedestrian Crash Data Study) cases with laboratory impact tests and computer simulations has been conducted. This paper presents the results of this research.

NHTSA uses a variety of computer modelling techniques to develop and evaluate test methods and mitigation concepts, and to estimate safety benefits for many of NHTSA's research activities. Computer modeling has been particularly beneficial for estimating safety benefits where often very little data are available. Also modeling allows researchers to augment test data by simulating crashes over a wider range of conditions than would otherwise be feasible. These capabilities are used for a wide range of projects from school bus to frontal, side, and rollover research programs. This paper provides an overview of these activities. NHTSA's most extensive modeling research involves developing finite element and articulated mass models to evaluate a range of vehicles and crash environments. These models are being used to develop a fleet wide systems model for evaluating compatibility issues.

This paper describes computer crash simulations performed by the National Highway Traffic Safety Administration (NHTSA) under the current research and testing activities on large school bus safety restraints. The simulations of a frontal rigid barrier test and comparative dynamic sled testing for compartmentalization, lap belt, and lap/shoulder belt restraint strategies are presented. School bus transportation is one of the safest forms of transportation in the United States. School age children transported in school buses are safer than children transported in motor vehicles of any other type. Large school buses provide protection because of their size and weight. Further, they must meet minimum Federal motor vehicle safety standards (FMVSSs) mandating compartmentalized seating, improved emergency exits, stronger roof structures and fuel systems, and better bus body joint strength.

A review was conducted of injuries associated with ejection through motor vehicle glazing, using the 1988 through 1991 National Accident Sampling System data maintained by the National Highway Traffic Safety Administration. The review indicated that one percent of the occupants in towaway crashes were ejected and that 22 percent of fatalities in towaway crashes were ejected. Fifty-three percent of complete ejections were through the glazing openings in motor vehicles. Current motor vehicle glazing does not contribute significantly to occupant injuries, but the effects of glazing changes on serious injuries will need to be considered.

This paper describes the contents, development, and use of the NHTSA's Vehicle Parameter Database in accident data analysis and injury determination. The database also can be used as a source for vehicle information for computer model/simulation programs or in the development of crash avoidance measures. The analyses of damage sustained by vehicles in accidents is based on post-crash information and is somewhat limited since pre-crash measurements are not usually known or readily available. The ability to compare pre-crash and post-crash basic vehicle measurement characteristics provides greater insight into analyzing vehicle damage, degree of intrusion, level of deformation, and injury severity/source. The Vehicle Parameter Database consists of 101 key vehicle dimensions and specifications on more than 2,800 vehicles from 1980 to 1994.

Computational simulations are conducted for several head impact scenarios using a three dimensional finite element model of the human brain in conjunction with accelerometer data taken from crash test data. Accelerometer data from a 3-2-2-2 nine accelerometer array, located in the test dummy headpart, is processed to extract both rotational and translational velocity components at the headpart center of gravity with respect to inertial coordinates. The resulting generalized six degree-of-freedom description of headpart kinematics includes effects of all head impacts with the interior structure, and is used to characterize the momentum field and inertial loads which would be experienced by soft brain tissue under impact conditions. These kinematic descriptions are then applied to a finite element model of the brain to replicate dynamic loading for actual crash test conditions, and responses pertinent to brain injury are analyzed.

As Intelligent Transportation Systems (ITS) become more prevalent, the need to archive data from field tests becomes more critical. These data can guide the design of future systems, provide an information conduit among the many developers of ITS, enable comparisons across locations and time, and support development of theoretical models of driver behavior. The National Highway Traffic Safety Administration (NHTSA) is interested in such an archive. While a design for an ITS data archive has not yet been developed, NHTSA has supported the enhancement of the Test Planning, Analysis, and Evaluation System (Test PAES), originally developed by Calspan SRL Corporation for the U. S. Air Force Armstrong Laboratory, for possible use in such an archive. On a single screen, Test PAES enables engineering unit data, audio, and video, as well as a vehicle animation, to be time synchronized, displayed simultaneously, and operated with a single control.

This paper reviews some of the progress that has been made in recent years in the transportation field by behavioral scientists and human factors engineers. The major areas covered are public transportation systems, railroad systems, highway systems, and personal transportation systems. The report suggests what future problems may be encountered in these areas that will need the attention of human factors specialists.

A comprehensive review of casualty-reducing effectiveness estimates of child safety seats in actual use, obtained by statistical analyses of highway accident data. Recent analyses of large samples of New York and Maryland accidents show statistically significant injury reductions for child safety seats; so does a new analysis of the National Highway Traffic Safety Administration's accident files. Results from Washington State, Tennessee, New Jersey, and Idaho are also reviewed, as are Nationwide restraint usage and fatality trends. The findings are critically examined for possible data biases. It is concluded that child safety seats definitely reduce deaths and injuries in highway crashes, but that their effectiveness cannot be accurately estimated at this time because of inconsistencies and possible biases in the various studies.

The computer program, CRASH 3, uses the equations of motion to estimate the changes in velocity of motor vehicles in crashes and their trajectories following a collision. It was developed in the mid-1970's by McHenry at Caispan for use in accident research. There are important limitations on where and how it should be used. CRASH 3 requires a skilled reconstruction of a crash and an interactive execution of the program to provide reasonably accurate results. The paper also discusses the sensitivity of CRASH 3 to various parameters and the potential for improving it. This paper presents the views of its author and not necessarily those of the National Highway Traffic Safety Administration (NHTSA).

The facial laceration test has been proposed as an addition to the dummy injury criteria of Federal Motor Vehicle Safety Standard 208. To better understand laceration conditions as they actually occur, three road crashes of increasing severity, all involving facial laceration by the broken (cracked) windshield and one involving partial ejection, have been simulated physically and analytically. The physical simulations used vehicle test bucks, the Hybrid III head with the chamois facial coverings of the facial laceration test, and a piston - constrained Head Impactor. Computer simulations of the three crashes were also carried out using the CALSPAN 3D “CVS” and the 2D “DRISIM” computer programs. The computer simulations provide insight into the effective mass of the head and body on windshield contact, and the forces, velocities, and accelerations involved.

This paper describes a Field Operational Test (FOT) of an Automated Collision Notification (ACN) System, a new way to provide definitive pre- hospital medical care to people injured in motor vehicle crashes. This FOT is part of the National Highway Traffic Safety Administration's (NHTSA's) research being conducted under the U.S. Department of Transportation's Intelligent Transportation Systems (ITS) program. Management of the program is by the Office of Vehicle Safety Research in NHTSA. The ACN FOT is a demonstration of the application of advanced technology for the improvement of pre-hospital emergency care for motor-vehicle crash victims. The test, involving approximately 850 volunteers' vehicles, was conducted in rural Western New York State. A partnership of local public agencies and private corporations, led by Veridian, Inc., performed the test.

This paper is primarily a printed listing of the National Highway Traffic Safety Administration’s (NHTSA) Light Vehicle Inertial Parameter Database. This database contains measured vehicle inertial parameters from SAE Paper 930897, “Measured Vehicle Inertial Parameters -NHTSA’s Data Through September 1992” (1), as well as parameters obtained by NHTSA since 1992. The proceeding paper contained 414 entries. This paper contains 82 new entries, for a total of 496. The majority of the entries contain complete vehicle inertial parameters, some of the entries contain tilt table results only, and some entries contain both inertia and tilt table results. This paper provides a brief discussion of the accuracy of inertial measurements. Also included are selected graphs of quantities listed in the database for some of the 1998 model year vehicles tested.

A methodology to develop full-vehicle representation in the form of a finite element model for crashworthiness studies has been evolved. Detailed finite element models of two passenger vehicles - 1995 Chevy Lumina and 1994 Dodge Intrepid have been created. The models are intended for studying the vehicle’s behavior in full frontal, frontal offset and side impact collisions. These models are suitable for evaluating vehicle performance and occupant safety in a wide variety of impact situations, and are also suitable for part and material substitution studies to support PNGV (Partnership for New Generation of Vehicles) research. The geometry for these models was created by careful scanning and digitizing of the entire vehicle. High degree of detail is captured in the BIW, the front-end components and other areas involved in frontal, frontal offset and side impact on the driver’s side.

With the emergence of Driving Automation Systems (SAE levels 1-5), the necessity arises for methods of evaluating these systems. However, these systems are much more challenging to evaluate than traditional safety features (SAE level 0). This is because an understanding of the Driving Automation system’s response in all possible scenarios is desired, but prohibitive to comprehensively test. Hence, this paper attempts to evaluate one such system, by modeling its behavior. The model generated parameters not only allow for objective comparison between vehicles, but also provide a more complete understanding of the system. The model can also be used to extrapolate results by simulating other scenarios without the need for conducting more tests. In this paper, low speed automated driving (also known as Traffic Jam Assist (TJA)) is studied. This study focused on the longitudinal behavior of automated vehicles while following a lead vehicle (LV) in traffic jam scenarios.