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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.

This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing.

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 paper discusses the importance of having an adequate model for the dynamic response characteristics of tire lateral force to steering inputs. Computer simulation and comparison with experimental results are used to show the importance of including appropriate tire dynamics in simulation tire models to produce accurate predictions of vehicle dynamics. Improvements made to the tire dynamics model of an existing vehicle stability and control simulation, the Vehicle Dynamics Analysis, Non-Linear (VDANL) simulation, are presented. Specifically, the improvements include changing the simulation's tire dynamics from first-order system tire side force lag dynamics to second-order system tire slip angle dynamics. A second-order system representation is necessary to model underdamped characteristics of tires at high speeds. Lagging slip angle (an input to the tire model) causes all slip angle dependent tire force and moment outputs to be lagged.

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.

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 process of testing a suspension on the Suspension Parameter Measurement Device (SPMD). It begins by discussing the process of preparing to test a suspension on the SPMD. This includes discussions of preparing a suspension identification data file, mounting the suspension to be tested on a buck, and the calibration of the SPMD's transducers. The next sections of the paper cover the actual testing performed on a suspension while it is mounted on the SPMD. The different types of suspension tests performed are described and the rationale for each type of test is discussed. The flowchart for a typical individual test is presented and explained. The matrix of individual tests performed for each suspension tested is discussed. Estimates of the time and manpower required to perform the testing are given. The paper next looks at the data measured by the SPMD. The first level of analysis performed on the data is explained.

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.

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 summarizes the results of test maneuvers devised to measure on-road, untripped, rollover propensity. Complete findings from this research are contained in [1]. Twelve test vehicles, representing a wide range of vehicle types and classes were used. Three vehicles from each of four categories: passenger cars, light trucks, vans, and sport utility vehicles, were tested. The vehicles were tested with vehicle characterization and untripped rollover propensity maneuvers. The vehicle characterization maneuvers were designed to determine fundamental vehicle handling properties while the untripped rollover propensity maneuvers were designed to produce two-wheel lift for vehicles with relatively higher rollover propensity potential. The vehicle characterization maneuvers were Pulse Steer, Sinusoidal Sweep, Slowly Increasing Steer, and Slowly Increasing Speed. The rollover propensity maneuvers were J-Turn, J-Turn with Pulse Braking, Fishhook #1 and #2, and Resonant Steer.

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.

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.

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.

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 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.

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].

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.

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.

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.