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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.

This research focuses on the development and performance of analytical models to simulate a tractor-semitrailer in straight-ahead braking. The simulations were modified and tuned to simulate full-treadle braking with all brakes functioning correctly, as well as the behavior of the tractor-semitrailer rig under full braking with selected brakes disabled. The models were constructed in TruckSim and based on a tractor-semitrailer used in dry braking performance testing. The full-scale vehicle braking research was designed to define limits for engineering estimates on stopping distance when Class 8 air-braked vehicles experience partial degradation of the foundation brake system. In the full scale testing, stops were conducted from 30 mph and 60 mph, with the combination loaded to 80,000 lbs (gross combined weight or GCW), half payload, and with the tractor-semitrailer unladen (lightly loaded vehicle weight, or LLVW).

Typical factors that contribute to the coast down characteristics of a vehicle include aerodynamic drag, gravitational forces due to slope, pumping losses within the engine, frictional losses throughout the powertrain, and tire rolling resistance. When summed together, these reactions yield predictable deceleration values that can be related to vehicle speeds. This paper focuses on vehicle decelerations while coasting with a typical medium-sized SUV. Drag factors can be classified into two categories: (1) those that are caused by environmental factors (wind and slope) and (2) those that are caused by the vehicle (powertrain losses, rolling resistance, and drag into stationary air). The purpose of this paper is to provide data that will help engineers understand and model vehicle response after loss of engine power.

This paper describes the development and implementation of an accurate and repeatable path-following algorithm focused ultimately on vehicle testing. A compact, lightweight, and portable hardware package allows easy installation and negligible impact on the vehicle mass, even for the smallest automobile. Innovative features include the ability to generate a smooth, evenly-spaced path vector regardless the quality of the given path. The algorithm proposed in this work is suitable for testing in a controlled environment. The system was evaluated in simulation and performed well in road tests at low speeds.

This paper presents an evaluation of a complete vehicle dynamics model for a 2006 BMW 330i to be used for the National Advanced Driving Simulator. Vehicle handling and braking are evaluated and simulation results are compared with experimental field-testing. NADSdyna, the National Advanced Driving Simulator vehicle dynamics software, is used. The BMW evaluation covers vehicle directional dynamics that include steady-state, transient, and frequency domain responses. These evaluations are performed with the DSC (Dynamic Stability and Control) turned off to ensure the principle mechanical properties of the vehicle are properly modeled before enabling the electronic stability system. The evaluation also includes simulation runs with DSC turned on for the J-turn and severe lane change maneuvers.

The intent of this research is to understand the effects worn dampers have on vehicle stability and safety through dynamic model simulation. Dampers, an integral component of a vehicle's suspension system, play an important role in isolating road disturbances from the driver by controlling the motions of the sprung and unsprung masses. This paper will show that a decrease in damping leads to excessive body motions and a potentially unstable vehicle. The concept of poor damping affecting vehicle stability is well established through linear models. The next step is to extend this concept for non-linear models. This is accomplished through creating a vehicle simulation model and executing several driving maneuvers with various damper characteristics. The damper models used in this study are based on splines representing peak force versus velocity relationships.

This paper describes the design and development of the hardware, electronics, and software components of a state-of-the-art automated steering controller, the SEA, Ltd. ASC. The function of the ASC is to input to a vehicle virtually any steering profile with both high accuracy and repeatability. The ASC is designed to input profiles having steering rates and timing that are in excess of the limits of a human driver. The ASC software allows the user to specify steering profiles and select controller settings, including motor controller gains, through user-interface windows. This makes it possible for the test driver to change steering profiles and settings immediately after running any test maneuver. The motor controller used in the ASC offers self-contained signal input, output, and data storage capabilities. Thus, the ASC can operate as a standalone steering machine or it can be incorporated into typical existing, on-vehicle data acquisition systems.

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.

During Phase VI of the National Highway Traffic Safety Administration's (NHTSA) Light Vehicle Rollover Research Program, three of the twenty-six light vehicles tested exhibited significant response asymmetries with respect to left versus right steer maneuvers. This paper investigates possible vehicle asymmetric characteristics and unintended inputs that may cause vehicle asymmetric response. An analysis of the field test data, results from suspension and steering parameter measurements, and a summary of a computer simulation study are also given.

This study involves two areas of research. The first is the finalization of the Pedestrian Crash Data Study (PCDS) in order to provide detailed information regarding the vehicle/pedestrian accident environment and how it has changed from the interim PCDS information. The pedestrian kinematics, injury contact sources, and injuries were analyzed relative to vehicle geometry. The second area presented is full-scale attempts at reconstruction of two selected PCDS cases using the Polar II pedestrian dummy to determine if the pre-crash motion of the pedestrian and vehicle could somehow be linked to the injuries and vehicle damage documented in the case.

The National Highway Traffic Safety Administration's Vehicle Research and Test Center (VRTC) plans to evolve the state-of-the-art of steering system modeling for driving simulators with the ultimate goal being the development of a high fidelity steering feel model for the National Advanced Driving Simulator (NADS). The VRTC plans on developing reliable research tools that can be used to determine the necessary features for a steering model that will provide good objective and subjective steering feel. This paper reviews past and continuing work conducted at the VRTC and provides a plan for future work that will achieve this goal.

This paper describes the design of a vehicle inertia measurement facility (VIMF): a facility used to measure vehicle center of gravity position; vehicle roll, pitch, and yaw mass moments of inertia; and vehicle roll/yaw mass product of inertia. The rationale for general design decisions and the methods used to arrive at the decisions are discussed. The design is inspired by the desire to have minimal measurement error and short test time. The design was guided by analytical error analyses of the contributions of individual system errors to the overall measurement error. A National Highway Traffic Safety Administration (NHTSA) database of center of gravity position and mass moment of inertia data for over 300 vehicles was used in conjunction with the error analyses to design various VIMF components, such as the roll and yaw spring sizes.

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.