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This paper presents a methodology for validating vehicle stability and control computer simulations. Validation is defined as showing that, within some specified operating range of the vehicle, a simulation's predictions of a vehicle's responses agree with the actual measured vehicle's responses to within some specified level of accuracy. The method uses repeated experimental runs at each test condition to generate sufficient data for statistical analyses. The acquisition and reduction of experimental data, and the processing path for simulation data, are described. The usefulness of time domain validation for steady state and slowly varying transients is discussed. The importance of frequency domain validation for thoroughly validating a simulation is shown. Both qualitative and quantitative methods for the comparison of the simulation predictions with the actual test measurements are developed.

The goal of this research was to find vehicle characteristics which may contribute to steering maneuver induced rollover accidents. This work involved studying vehicle handling dynamics using the Vehicle Dynamics Analysis, Non-Linear (VDANL) computer simulation. The simulation was used to predict vehicle responses while performing 28 different steering induced maneuvers for each of 51 vehicles. Various measures of vehicle response (metrics), such as response times, percent overshoots, etc., were computed for each vehicle from simulation predictions. These vehicle directional response metrics were analyzed in an attempt to identify vehicle characteristics that might be good predictor/explanatory variables for vehicle rollover propensity. The metrics were correlated, using the Statistical Analysis System (SAS) software and logistic regression, with single vehicle accident data from the state of Michigan for the years 1986 through 1988.

Two computer models of drivers using describing function strategies have been successfully implemented in conjunction with a recently developed, all digital vehicle simulation. The driver models determine control inputs to the vehicle simulation by means of feedback loops. Two feedback loops, an outer one on lateral position and an inner one on heading angle are used to determine the steering commands needed to move the vehicle to the desired path. One feedback loop on forward velocity is used to determine braking and acceleration commands. Full technical details of the method of implementation for each of the models are given. The results of sample simulations of the driver-vehicle system are shown and the results discussed.

Two computer models of drivers using preview predictor strategies have been successfully implemented in conjunction with a recently developed, all digital vehicle simulation. The driver models determine control inputs to the vehicle simulation by first predicting future vehicle position and velocity and then determining the steering and braking commands necessary to move the vehicle from the predicted to the desired path. Full technical details of the method of implementation for each of the models are given. The results of sample simulations of the driver-vehicle system using each driver model are shown. Problems of each model are discussed.

This paper is primarily a printed listing of the National Highway Traffic Safety Administration's (NHTSA) Light Vehicle Inertial Parameter Data Base. This data base contains measured vehicle inertial parameters from all of the 356 tests performed to date with NHTSA's Inertial Parameter Measurement Device (IPMD) that have resulted in data thought to be of general interest. Additionally, the data base contains tilt table data from all 168 vehicle tests performed to date using NHTSA's Tilt Table. The paper also summarizes the history of modifications to the IPMD and discusses how these modifications have improved the accuracy of IPMD measurements.

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.

This paper presents an overview of work performed by the National Highway Traffic Safety Administration's (NHTSA) Vehicle Research and Test Center (VRTC) to test, validate, and improve the planned National Advanced Driving Simulator's (NADS) vehicle dynamics simulation. This vehicle dynamics simulation, called NADSdyna, was developed by the University of Iowa's Center for Computer-Aided Design (CCAD) NADSdyna is based upon CCAD's general purpose, real-time, multi-body dynamics software, referred to as the Real-Time Recursive Dynamics (RTRD), supplemented by vehicle dynamics specific submodules VRTC has “beta tested” NADSdyna, making certain that the software both works as computer code and that it correctly models vehicle dynamics. This paper gives an overview of VRTC's beta test work with NADSdyna. The paper explains the methodology used by VRTC to validate NADSdyna.

Driver distraction has been identified as a high-priority topic by the National Highway Traffic Safety Administration, reflecting concerns about the compatibility of certain in-vehicle technologies with the driving task, whether drivers are making potentially dangerous decisions about when to interact with in-vehicle technologies while driving, and that these trends may accelerate as new technologies continue to become available. Since 1991, NHTSA has conducted research to understand the factors that contribute to driver distraction and to develop methods to assess the extent to which in-vehicle technologies may contribute to crashes. This paper summarizes significant findings from past NHTSA research in the area of driver distraction and workload, provides an overview of current ongoing research, and describes upcoming research that will be conducted, including research using the National Advanced Driving Simulator and work to be conducted at NHTSA’s Vehicle Research and Test Center.

The National Highway Traffic Safety Administration (NHTSA) has proposed building the National Advanced Driving Simulator (NADS). As proposed, the NADS will move the simulator's cab so that realistic motion cues are provided to the simulator's driver. It is necessary to determine the motion base capabilities that the NADS will need to simulate different severities and types of driving maneuvers with adequate simulated motion fidelity. The objectives of this study were (1) to develop tools, based on existing vehicle dynamics simulations, simulator washout algorithms, and human perceptual models, that allow required motion base capabilities to be determined and (2) to use these tools to perform analyses that determine the motion base capabilities needed by the NADS. The NADS motion base configuration examined during this study, which may not correspond to that used when the NADS is actually constructed, includes an X-Y Carriage capable of large excursions.

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 describes the theory and design of an apparatus, the Suspension Parameter Measurement Device (SPMD), which has been developed to measure the displacements and forces which occur at the road wheels of a vehicle as the body moves, or as lateral and/or longitudinal forces are applied at the tire/road interface. Wheel movements resulting from the bounce, pitch, or roll motions of the vehicle body in the absence of lateral and longitudinal forces at the tire/road interface are the kinematic characteristics of the suspension. Wheel displacements caused by the application of forces in the plane of the road are defined as the compliance characteristics, while those resulting from motions of the steering wheel are the steering characteristics. The purpose of the SPMD is to measure all of these characteristics, thereby providing data for use in the simulation of the performance of cars and light trucks.

This paper describes an apparatus, called the Inertial Parameter Measurement Device (IPMD), which recently has been developed by the National Highway Traffic Safety Administration at its Vehicle Research and Test Center. The IPMD measures the center of gravity height and the pitch, roll, and yaw moments of inertia of a vehicle. The first section of this paper describes the features, capabilities, limitations, and design of the IFMD. This is followed by a presentation of the vehicle parameters that have been measured by it, to date. The final section of the paper presents several commonly used, and one proposed, rules of thumb for estimating inertial parameters. Data from measurements made by the IPMD are used to show the validity of these rules. Curves obtained by fitting the measured data are also shown for the moments of inertia as functions of the vehicle weight.