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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.

In crashes between heavy trucks and light vehicles, most of the fatalities are the occupants of the light vehicle. A reduction in heavy truck stopping distance should lead to a reduction in the number of crashes, the severity of crashes, and consequently the numbers of fatalities and injuries. This study made use of the National Advanced Driving Simulator (NADS). NADS is a full immersion driving simulator used to study driver behavior as well as driver-vehicle reactions and responses. The vehicle dynamics model of the existing heavy truck on NADS had been modified with the creation of two additional brake models. The first was a modified S-cam (larger drums and shoes) and the second was an air-actuated disc brake system. A sample of 108 CDL-licensed drivers was split evenly among the simulations using each of the three braking systems. The drivers were presented with four different emergency stopping situations.

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 examines variability of two static rollover metrics, Static Stability Factor (SSF) and Tilt Table Ratio (TTR), due to vehicle loading and vehicle-to-vehicle variation. Variability due to loading was determined by measuring SSF and TTR for 14 vehicles/configurations at multiple loadings. Up to five loadings were used per vehicle/configuration tested. Vehicle-to-vehicle variability was studied by measuring SSF and TTR for ten unmodified vehicles of each of four make/models. Five baseline vehicles, as similar as was feasible, were tested. The other five test vehicles spanned the range of submodels and options available. In general, both SSF and TTR decreased as occupants were added to a vehicle. The change in SSF and TTR per occupant was fairly consistent, with changes in TTR being more consistent. Placing ballast on the floor of the cargo compartment had a mixed effect on SSF, raising it for some vehicles and lowering it for others.

This research studied the problems and effectiveness of existing cross view school bus mirror systems. Interviews were conducted with 49 school bus drivers to ascertain their evaluations of the use and perceived effectiveness of various cross view mirror systems. Six commercially available cross view mirrors were randomly selected for testing. These mirrors were used to make the seven cross view mirror systems (each with 2 to 4 cross view mirrors) which were evaluated. The optical properties of each cross view mirror and the field of view (FOV) of each mirror system were measured in a laboratory environment. Mirror system FOVs were determined with the mirrors mounted on each of three different types of school buses. The directly observable FOV of each bus was also determined. Driver child detection field studies were conducted using eight bus drivers and six mirror systems with simulated children.

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.

Side object detection systems (SODS) are collision warning systems which alert drivers to the presence of traffic alongside their vehicle within defined detection zones. The intent of SODS is to reduce collisions during lane changes and merging maneuvers. This study examined the effect of right SODS on the performance of commercial vehicle drivers as a means of assessing the impact of these systems on safety. In this study, eight professional truck drivers drove a tractor-semitrailer equipped with four different sets of SODS hardware or side view mirror configurations. These subjects had no previous experience with SODS. Subjects were tested with two right SODS (a radar-based system and an ultrasonic-based system), a fender-mounted convex mirror, and, for comparison, standard side view mirrors only. For each case, subjects drove the test vehicle through a set route for one day.

This paper describes the assessment of driver interfaces of a type of electronics-based collision avoidance systems that has been recently developed to assist drivers of vehicles in avoiding certain types of collisions. The electronics-based crash avoidance systems studied were those which detect the presence of objects located on the left and/or right sides of the vehicle, called Side Collision Avoidance Systems, or SCAS. As many SCAS as could be obtained, including several pre-production prototypes, were acquired and tested. The testing focused on measuring sensor performance and assessing the qualities of the driver interfaces. This paper presents only the results of the driver interface assessments. The sensor performance data are presented in the NHTSA report “Development of Performance Specifications for Collision Avoidance Systems for Lane Changing, Merging, and Backing - Task 3 - Test of Existing Hardware Systems” [1].

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 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.

Most fatalities due to school bus accidents involve pedestrians being struck by the bus. All too frequently the school bus strikes a disembarking passenger because the driver was unaware of their presence near the bus. To try to prevent this type of accident, two Doppler microwave radar-based pedestrian detection systems have been developed and are commercially available. These systems supplement regular school bus mirrors. They operate only while the bus is stationary. Both systems detect moving pedestrians either directly in front of or to the right of the bus. The National Highway Traffic Safety Administration has performed a three-part evaluation of these pedestrian detection systems. The first part measured the field of view of each system's sensors. The second part evaluated the effectiveness and appropriateness of each system's driver interface. The third part was a small-scale operational evaluation.

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.

According to NHTSA's 2011 Traffic Safety Facts [1], passenger vehicle occupant fatalities continued the strong decline that has been occurring recently. In 2011, there were 21,253 passenger vehicles fatalities compared to 22,273 in 2010, and that was a 4.6% decrease. However; large-truck occupant fatalities increased from 530 in 2010 to 635 in 2011, which is a 20% increase. This was a second consecutive year in which large truck fatalities have increased (9% increase from 2009 to 2010). There was also a 15% increase in large truck occupant injuries from 2010. Moreover, the fatal crashes involving large trucks increased by 1.9%, in contrast to other-vehicle-occupant fatalities that declined by 3.6% from 2010. The 2010 accident statistics NHTSA's report reveals that large trucks have a fatal accident involvement rate of 1.22 vehicles per 100 million vehicle miles traveled compared to 1.53 for light trucks and 1.18 for passenger cars.

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.