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Torsional stiffness properties were developed for both a 53-foot box trailer and a 28-foot flatbed control trailer based on experimental measurements. In order to study the effect of torsional stiffness on the dynamics of a heavy truck vehicle dynamics computer model, static maneuvers were conducted comparing different torsional stiffness values to the original rigid vehicle model. Stiffness properties were first developed for a truck tractor model. It was found that the incorporation of a torsional stiffness model had only a minor effect on the overall tractor response for steady-state maneuvers up to 0.4 g lateral acceleration. The effect of torsional stiffness was also studied for the trailer portion of the existing model.

The rapid innovation underway with vehicle brake safety systems leads to extensive evaluation and testing by system developers and regulatory agencies. The ability to evaluate complex heavy truck braking systems is potentially more rapid and economical through hardware-in-the-loop (HiL) simulation which employs the actual electronics and vehicle hardware. Though the initial HiL system development is time consuming and expensive, tests conducted on the completed system do not require track time, fuel, vehicle maintenance, or technician labor for driving or truck configuration changes. Truck and trailer configuration and loading as well as test scenarios can be rapidly adjusted within the vehicle dynamics simulation software to evaluate the performance of automated safety interventions (such as ESC) over a wide range of conditions.

The tractor trailer models discussed in this paper were for a real-time hardware-in-the-loop (HIL) simulation to test heavy truck electronic stability control (ESC) systems [1]. The accuracy of the simulation results relies on the fidelity and accuracy of the vehicle parameters used. However in this case where hardware components are part of the simulation, their accuracy also affects the proper working of the simulation and ESC unit. Hence both the software and hardware components have to be validated. The validation process discussed in this paper is divided into two sections. The first section deals with the validation of the TruckSim vehicle model, where experimental data is compared with simulation results from TruckSim. Once the vehicle models are validated, they are incorporated in the HIL simulation and the second section discusses the validation of the whole HIL system with ESC.

The paper discusses the development of a model for the 2006 BMW 330i for the National Advanced Driving Simulator's (NADS) vehicle dynamics simulation, NADSdyna. The front and rear suspensions are independent strut and link type suspensions modeled using recursive rigid-body dynamics formulations. The suspension springs and shock absorbers are modeled as force elements. The paper includes parameters for front and rear semi-empirical tire models used with NADSdyna. Longitudinal and lateral tire force plots are also included. The NADSdyna model provides state-of-the-art high-fidelity handling dynamics for real-time hardware-in-the-loop simulation. The realism of a particular model depends heavily on how the parameters are obtained from the actual physical system. Complex models do not guarantee high fidelity if the parameters used were not properly measured. Methodologies for determining the parameters are detailed in this paper.

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.

In 2007, a software model of a Roll Stability Control (RSC) system was developed based on test data for a Volvo tractor at NHTSA's Vehicle Research and Test Center (VRTC). This model was designed to simulate the RSC performance of a commercially available Electronic Stability Control (ESC) system. The RSC model was developed in Simulink and integrated with the available braking model (TruckSim) for the truck. The Simulink models were run in parallel with the vehicle dynamics model of a truck in TruckSim. The complete vehicle model including the RSC system model is used to simulate the behavior of the actual truck and determine the capability of the RSC system in preventing rollovers under different conditions. Several simulations were performed to study the behavior of the model developed and to compare its performance with that of an actual test vehicle equipped with RSC.

Validation was performed on an existing heavy truck vehicle dynamics computer model with roll stability control (RSC). The first stage in this validation was to compare the response of the simulated tractor to that of the experimental tractor. By looking at the steady-state gains of the tractor, adjustments were made to the model to more closely match the experimental results. These adjustments included suspension and steering compliances, as well as auxiliary roll moment modifications. Once the validation of the truck tractor was completed for the current configuration, the existing 53-foot box trailer model was added to the vehicle model. The next stage in experimental validation for the current tractor-trailer model was to incorporate suspension compliances and modify the auxiliary roll stiffness to more closely model the experimental response of the vehicle. The final validation stage was to implement some minor modifications to the existing RSC model.

This paper presents the details of the model for the physical steering system used on the National Advanced Driving Simulator. The system is basically a hardware-in-the-loop (steering feedback motor and controls) steering system coupled with the core vehicle dynamics of the simulator. The system's torque control uses cascaded position and velocity feedback and is controlled to provide steering feedback with variable stiffness and dynamic properties. The reference model, which calculates the desired value of the torque, is made of power steering torque, damping function torque, torque from tires, locking limit torque, and driver input torque. The model also provides a unique steering dead-band function that is important for on-center feel. A Simulink model of the hardware/software is presented and analysis of the simulator steering system is provided.

The paper discusses the development of a model for a 1998 Chevrolet Malibu for the National Advanced Driving Simulator’s (NADS) vehicle dynamics simulation, NADSdyna. The Malibu is the third vehicle modeled for the NADS, and this is the third paper dealing with model development. SAE Paper 970564 contains details of the model for the 1994 Ford Taurus and SAE Paper 1999–01-0121 contains details of the model for the 1997 Jeep Cherokee. The front and rear suspensions are independent strut and link type suspensions modeled using recursive rigid body dynamics formulations. The suspension springs and shock absorbers are modeled as elements in the rigid body formulation. To complement the vehicle dynamics for the NADS application, subsystem models that include tire forces, braking, powertrain, aerodynamics, and steering are added to the rigid body dynamics model. The models provide state-of-the-art high fidelity vehicle handling dynamics for real-time simulation.

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 focuses on the overall structure of the Crash Injury Research and Engineering Network (CIREN), how data are collected, and what makes it unique. It discusses how it can be used to expand and enhance the information in other databases. CIREN is a collaborative effort to conduct research on crashes and injuries at nine Level 1 Trauma Centers which are linked by a computer network. Researchers can review data and share expertise, which will lead to a better understanding of crash injury mechanisms and the design of safer vehicles. CIREN data are being used in outreach and education programs on motor vehicle safety. CIREN outreach and education has already been credited with lifesaving information dissemination.

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.

This paper presents the development of a real-time vehicle dynamics model of the heavy tractor-trailer combination used in the National Advanced Driving Simulator. The model includes multi-body dynamics of the tractor and trailer chassis, suspension, and steering mechanisms. The rigid body model is formulated using recursive multi-body dynamics code. This model is augmented with subsystem models that include tires, leaf springs, brakes, steering system, and aerodynamic drag. This paper also presents parameter measurement and estimations used to set up the model. Also included are models for brake fade, steering torque resistance, and defective tires.

This paper attempts to define and measure factors related to a vehicle's performance that are influential in the causation of rollover accidents. Data are presented which define the rollover involvement rates for many non-vehicular factors. A brief description of the vehicle metrics and the analysis procedures used in the rollover prevention rulemaking program are included along with a set of conclusions. The program evaluated many vehicle metrics related to vehicle rollover, analyzed accidents from 5 states, and compared the two data bases by testing “cause and effect” hypotheses by performing statistical regressions to determine levels of correlation. Location of the crash, urban vs. rural, was a strong predictor of the crash outcome - that is, rollover or non-rollover. Vehicle class and single vehicle accident rate were also statistically significant, as well as, whether or not the vehicle was equipped with anti-lock brakes. Several other driver demographics were significant.

When a heavy vehicle driver (or in fact a driver of any vehicle) makes a brake application that is too "hard" for conditions - especially when the vehicle is lightly loaded or empty and/or the road is wet or slippery - he is likely to lock some or all of his wheels. Under these conditions, the tractor can jackknife or the trailer can swing out of its lane (if it is a combination-unit vehicle) or the truck can spin out (if it is a single-unit vehicle). Incorporation of an antilock brake system addresses the wheel lock and resultant control loss.

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.

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.