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Modern passenger cars are being equipped with advanced driver assistance systems such as lane departure warning, collision avoidance systems, adaptive cruise control, etc. Testing for operation and effectiveness of these warning systems involves interaction between vehicles. While dealing with multiple moving vehicles, obtaining discriminatory results is difficult due to the difficulty in minimizing variations in vehicle separation and other parameters. This paper describes test strategies involving an automated test driver interacting with another moving vehicle. The autonomous vehicle controls its state (including position and speed) with respect to the target vehicle. Choreographed maneuvers such as chasing and overtaking can be performed with high accuracy and repeatability that even professional drivers have difficulty achieving. The system is also demonstrated to be usable in crash testing.

There have been a number of papers written about the dynamic effects of low speed front to rear impacts between motor vehicles during the last several years. This has been an important issue in the field of accident analysis and reconstruction because of the frequency with which the accidents occur and the costs of injuries allegedly associated with them. Sideswipe impacts are another, often minor, type of motor vehicle impact that generate a significant number of injury claims. These impacts are difficult to analyze for a number of reasons. First, there have been very few studies in the literature describing the specific dynamic effects of minor sideswipe impacts on the struck vehicles and their occupants. Those that have been performed have focused on the impact of two passenger cars.

Despite efforts by industry to reduce the problem of injury in rear impacts, there continues to be a large number of such claims. This is true even in low speed impacts which result in little or no damage to the vehicles involved. Recent studies of such incidents have been described in the literature. These studies have concentrated primarily on simple bumper to bumper impacts where the front bumper of the striking vehicle contacts the rear bumper of the struck vehicle. Perhaps a more common type of rear impact is one in which the bumper of the striking vehicle rides over or under the rear bumper of the struck vehicle. The heavy truck to car rear impact is an example of an overriding impact. This paper describes several staged impacts of this type in which vehicle and occupant responses were measured using fully instrumented Hybrid III dummies or human volunteers.

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.

Following many accidents, one of the involved vehicles is found with partial or total separation of one of its wheels. In many such cases, forensic evidence on the wheel, and/or on some surface struck by the wheel, provide direct evidence that the wheel separation resulted from the impact. However, in some cases such direct evidence is not as obvious or cannot be identified. In those cases, it is often asserted that before the accident occurred one of the involved vehicles might have undergone a sudden loss of control as a result of a spontaneous partial or total wheel separation. This paper examines the response of rear wheel drive vehicles when there is a failure involving a ball joint on the front suspension as the vehicle is traveling along a roadway. The design of the front suspension is analyzed to determine the expected effects of such failure on the wheel geometry and on the interaction between the tires and the pavement.

This paper discusses the development of the 1997 Jeep Cherokee model for the National Advanced Driving Simulator's planned vehicle dynamics software, NADSdyna. Recursive rigid body formalism called the Real Time Recursive Dynamics (RTRD) developed by the University of Iowa is used to model the front and rear suspension mechanisms. To complement vehicle dynamics for simulator applications, subsystems that include tires, aerodynamics, powertrain, brake, and steering are added to the rigid body dynamics model. These models provide high fidelity driving realism to simulate severe handling maneuvers in real time. The soundness of the model does not only depend on the mathematics of the model, but also on the validity of the parameters. Therefore, this paper discusses thoroughly the methodology of parameters estimation. A generic model of cruise control is included.

The paper discusses the development of a vehicle dynamics model and model validation of the 2003 Ford Expedition in CarSim. The accuracy of results obtained from simulations depends on the realism of the model which in turn depends on the measured data used to define the model parameters. The paper describes the tests used to measure the vehicle data and also gives a detailed account of the methodology used to determine parameters for the CarSim Ford Expedition model. The vehicle model was validated by comparing simulation results with experimental testing. Bounce and Roll tests in CarSim were used to validate the suspension and steering kinematics and compliances. Field test data of the Sine with Dwell maneuver was used for the vehicle model validation. The paper also discusses the development of a functional electronic stability control system and its effect on vehicle handling response in the Sine with Dwell maneuver.

The paper discusses the development of a model of the 2003 Ford Expedition using ADAMS View and its validation with experimental data. The front and rear suspensions are independent double A-arm type suspensions modeled using rigid links and ideal joints. The suspension springs and shock absorbers are modeled as force elements. The plots comparing the experimental tests and the simulation results are shown in this paper. Quasi-static roll and bounce tests are used to validate the suspension characteristics of the model while the Sine with Dwell and Slowly Increasing Steer maneuvers are used to validate the vehicle handling and tire-road interaction characteristics of the model. This paper also details the incorporation of an ESC model, originally developed by Kinjawadekar et al. [2] for CarSim, with the ADAMS model. The ESC is modeled in Simulink and co-simulated with the ADAMS vehicle model. Plots validating the ESC model with experimental data are also included.

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.

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.

The severity of an impact in terms of the acceleration in the occupant compartment is dependent not only on the change in vehicle velocity, but also the time for the change in velocity to occur. These depend on the geometry and stiffness of both the striking vehicle and struck object. In narrow-object frontal impacts, impact location can affect the shape and duration of the acceleration pulse that reaches the occupant compartment. In this paper, the frontal impact response of a full-sized pickup to 10 mile per hour and 20 mile per hour pole impacts at the centerline and at a location nearer the frame rails is compared using the acceleration pulse shape, the average acceleration in the occupant compartment, and the residual crush. A bilinear curve relating impact speed to residual crush is developed.

The shape of an acceleration pulse in an impact is not only affected by the change in velocity, but also by the geometry and stiffness of the both the striking vehicle and the struck object. In this paper, the frontal crash performance of a full-size pickup is studied through a series of impact tests with a rigid pole and with a flat barrier. Each rigid pole test is conducted at one of four locations across the front of the vehicle and at impact speeds of 10 mph, 20 mph, or 30 mph. The flat barrier tests are conducted at 10 mph, 15 mph, 20 mph, and 30 mph. The vehicle crush and acceleration pulses resulting from the pole tests are compared to those resulting from the barrier tests. The severity of pole impacts and the severity of flat barrier impacts are compared based on peak accelerations and pulse durations of the occupant compartment.

A two-degree-of-freedom Roll Simulator has been developed to study the occupant kinematics of Recreational Off-Highway Vehicles (ROVs). To validate the roll simulator, test data was collected on a population of ROVs on the market today. J-turn maneuvers were performed to find the minimum energy limits required to tip up the vehicles. Two sets of tests were performed: for the first set, 10 vehicles were tested, where the motion was limited by safety outriggers to 10-15 degrees of roll; and for the second set, three of these vehicles were re-tested with outriggers removed and the vehicle motion allowed to reach 90 degrees of roll. These quarter-turn rollover tests were performed autonomously using an Automatic Steering Controller (ASC) and a Brake and Throttle Robot (BTR). Lateral and longitudinal accelerations as well as roll rate and roll angle were recorded for all tests.

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.

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 an evaluation of a vehicle dynamics model intended to be used for the National Advanced Driving Simulator (NADS). Dynamic validation for high performance simulation is not merely a comparison between experimental and simulation plots. It involves strong insight of vehicle's subsystems mechanics, limitations of the mathematical formulations, and experimental predictions. Lateral, longitudinal, and ride dynamics are evaluated using field test data, and analytical diagnostics. The evaluation includes linear and non-linear range of vehicle dynamics response.

There is currently a considerable effort being devoted to the development of anthropomorphic test devices for the measurement of thoracic side impact response. Both the SID and EUROSID have been proposed as viable candidates for this test device. In addition, the thorax of the three year old Fart 572 has been shown to be useful in simulating side impact while used in the frontal orientation. This apparent anomaly suggests that the intuitive differences between the frontal and side geometries of the thorax may not be significant. To date, all useable thoracic models have been unidirectional. For the most part, these have been frontal models. This paper discusses some of the difficulties inherent in the development of a two dimensional thoracic model and ways these difficulties can be addressed. Based on these considerations, a single thoracic impact model is proposed for simulation of both frontal and lateral impact without adjustment of model parameters for impact direction.

This paper documents the vehicle response of a tractor-semitrailer following a sudden air loss (Blowout) in a steer axle tire while traveling at highway speeds. The study seeks to compare full-scale test data to predicted response from detailed heavy truck computer vehicle dynamics simulation models. Full-scale testing of a tractor-semitrailer experiencing a sudden failure of a steer axle tire was conducted. Vehicle handling parameters were recorded by on-board computers leading up to and immediately following the sudden air loss. Inertial parameters (roll, yaw, pitch, and accelerations) were measured and recorded for the tractor and semitrailer, along with lateral and longitudinal speeds. Steering wheel angle was also recorded. These data are presented and also compared to the results of computer simulation models. The first simulation model, SImulation MOdel Non-linear (SIMON), is a vehicle dynamic simulation model within the Human Vehicle Environment (HVE) software environment.

Vehicular accidents occur in everyday life. Their degree of severity is often perceived by the general public based on the amount of human bodily injuries sustained. Nevertheless, accident reconstructionists measure the degree of severity of vehicular accidents by calculating terms that are called Collision Parameters. The principal objective of this paper is to describe the significance of the Collision Parameters and explain the vocabulary of accident reconstruction. A non-mathematical approach is utilized to provide a thorough understanding for the general public.

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.