Search Results

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.

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 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.

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.

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.

This paper focuses on two types of electronics-based object detection systems for heavy truck applications: those sensing the presence of objects to the rear of the vehicle, and those sensing the presence of objects on the right side of the vehicle. The rearward sensing systems are intended to aid drivers when backing their vehicles, typically at very low “crawl” speeds. Six rear object detection systems that were commercially available at the time that this study was initiated were evaluated. The right side looking systems are intended primarily as supplements to side view mirror systems and as an aid for detecting the presence of adjacent vehicles when making lane changes or merging maneuvers. Four side systems, two commercially available systems and two prototypes, were evaluated.

This paper presents the methodology and initial results of an effectiveness estimation effort applied to lane change crash avoidance systems. The lane change maneuver was considered to be composed of a decision phase and an execution phase. The decision phase begins when the driver desires to perform a lane change. It continues until the driver turns the handwheel to move the vehicle laterally into the new lane or until the driver decides to postpone the lane change. During the decision phase, the driver gathers information about the road scene ahead and either present or upcoming traffic or obstacles in the destination lane. The execution phase begins when the driver starts the move into the new lane and continues until the vehicle has been laterally stabilized in the destination lane. If the driver aborts the lane change once started, the maneuver execution phase concludes when the vehicle has been laterally stabilized in the original lane.

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.

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.