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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.

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.

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 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.

This paper describes and compares three methods of estimating the static rollover threshold of passenger cars and light trucks. The Static Stability Factor (SSF), Side Pull Ratio (SPR), and Tilt Table Ratio (TTR) “metrics” are described and methods of measuring each are presented. The comparison of the three metrics is limited to the accuracy, repeatability, and ease of the measurements, and does not attempt to compare their ability to predict real world rollover accident involvement. The results of the comparison have shown that the three metrics are very closely related. Based on this, the rollover accident predictive power of each metric is expected to be similar. However, the ease and accuracy of the TTR measurement make it the most useful of the three. DURING THE 1980's, the use of light trucks and multi-purpose vehicles for basic transportation increased considerably. By 1990, domestic full-size pickup trucks were regularly among the top five passenger vehicles sold.

This research was performed using a designed experiment to evaluate the loss of dry surface braking performance and stability that could be associated with the disablement of specific brake positions on a tractor-semitrailer. The experiment was intended to supplement and update previous research by Heusser, Radlinski, Flick, and others. It also sought to establish reasonable limits for engineering estimates on stopping performance degradation attributable to partial or complete brake failure of individual S-cam air brakes on a class 8 truck. Stopping tests were conducted from 30 mph and 60 mph, with the combination loaded to GCW (80,000 lb.), half-payload, and with the flatbed semitrailer unladen. Both tractor and semitrailer were equipped with antilock brakes. Along with stopping distance, brake pressures, longitudinal acceleration, road wheel speed, and steering wheel position and effort were also recorded.

This paper discusses the improvement of a heavy truck anti-lock brake system (ABS) model currently used by the National Highway Traffic Safety Administration (NHTSA) in conjunction with multibody vehicle dynamics software. Accurate modeling of this complex system is paramount in predicting real-world dynamics, and significant improvements in model accuracy are now possible due to recent access to ABS system data during on-track experimental testing. This paper focuses on improving an existing ABS model to accurately simulate braking under limit braking maneuvers on high and low-coefficient surfaces. To accomplish this, an ABS controller model with slip ratio and wheel acceleration thresholds was developed to handle these scenarios. The model was verified through testing of a Class VIII 6×4 straight truck. The Simulink brake system and ABS model both run simultaneously with TruckSim, with the initialization and results being acquired through Matlab.

This paper describes the mechanical design of a Suspension Parameter Identification Device and Evaluation Rig (SPIDER) for wheeled military vehicles. This is a facility used to measure quasi-static suspension and steering system properties as well as tire vertical static stiffness. The machine operates by holding the vehicle body nominally fixed while hydraulic cylinders move an “axle frame” in bounce or roll under each axle being tested. The axle frame holds wheel pads (representing the ground plane) for each wheel. Specific design considerations are presented on the wheel pads and the measurement system used to measure wheel center motion. The constraints on the axle frames are in the form of a simple mechanism that allows roll and bounce motion while constraining all other motions. An overview of the design is presented along with typical results.

Adequacy of resistance spot welds in low carbon steels in relation to structural integrity can become an issue in the reconstruction of automotive accidents. Because formation of a plug (or button or slug) in a peel test is used as a quality control criterion for welds, it is sometimes assumed conversely that a weld which failed is defective if no plug is present. Spot welds do not necessarily form a plug when fractured. Fracture behavior of spot welds both by overload and fatigue is reviewed. Then techniques for examination of field failures are discussed. Finally two case histories are discussed.

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.

Vehicle dynamics models employed in heavy truck simulation often treat the semitrailer as a torsionally rigid member, assuming zero deflection along its longitudinal axis as a moment is applied to its frame. Experimental testing, however, reveals that semitrailers do twist, sometimes enough to precipitate rollover when a rigid trailer may have remained upright. Improving the model by incorporating realistic trailer roll stiffness values can improve assessment of heavy truck dynamics, as well as an increased understanding of the effectiveness of stability control systems in limit handling maneuvers. Torsional stiffness measurements were conducted by the National Highway Traffic Safety Administration (NHTSA) for eight semitrailers of different types, including different length box vans, traditional and spread axle flat beds, and a tanker.

The objective of this paper is to develop a self-tuning optimal control of an active suspension. An active suspension composed of an identifier and a controller is proposed in this paper. Although control strategies on active (or semi-active) suspensions have been investigated during the past few decades, some problems are not well understood yet. One of them arising from the ride control of an active suspension is that when the weight and the moments of inertia of the sprung mass are varied, the feedback gains of the controller should vary with the variation of parameters accordingly. Therefore, the identifier is proposed before the controller is designed. In the real situations, the parameter variation may occur when loadings on vehicles vary - either from passengers or payloads, especially, in the case of loading on a truck. An identification structure using parallel model reference adaptive system (MRAS) is proposed to identify the true parameters.

This study was performed to showcase the possible applications of the Hardware-in-the-loop (HIL) simulation environment developed by the National Highway Traffic Safety Administration (NHTSA), to test heavy truck crash avoidance safety systems. In this study, the HIL simulation environment was used to recreate a simulation of an actual accident scenario involving a single tractor semi-trailer combination. The scenario was then simulated with and without an antilock brake system (ABS) and electronic stability control (ESC) system to investigate the crash avoidance potential afforded by the tractor equipped with the safety systems. The crash scenario was interpreted as a path-following problem, and three possible driver intended paths were developed from the accident scene data.

In 2004, a model of a 6s6m ABS controller was developed in order to support NHTSA's efforts in the study of heavy truck braking performance. This model was developed using Simulink and interfaced with TruckSim, a vehicle dynamics software package, in order to create an accurate braking simulation of a 6×4 Peterbilt straight truck. For this study, the vehicle model braking dynamics were improved and the ABS controller model was refined. Also, the controller was made adaptable to ABS configurations other than 6s6m, such as 4s4m and 4s3m. Controller models were finally validated to experimental data from the Peterbilt truck, gathered at NHTSA's Vehicle Research and Test Center (VRTC).

Accident reconstructionists use several different approaches to determine vehicle equivalent impact speed from damage due to narrow object impacts. One method that is used relates maximum crush to equivalent impact speed with a bilinear curve. In the past, this model has been applied to several passenger cars with unibody construction. In this paper, the approach is applied to a body-on-frame vehicle. Several vehicle-to-rigid pole impact tests have been conducted on a full-size pickup at different speeds and impact locations: centrally located across the vehicle's front and outside the frame rail. A bilinear model relating vehicle equivalent impact speed to maximum crush is developed for the impact locations. These results are then compared to results obtained from other body-on-frame vehicles as well as unibody vehicles. Other tests such as impacts on the frame rail and barrier impacts are also presented. Limitations to this bilinear approach are discussed.

This paper introduces a new nonlinear model for simulating the dynamics of pneumatic-over-mechanical commercial vehicle braking systems. The model employs an effective systems approach to accurately reproduce forcing functions experienced at the hubs of heavy commercial vehicles under braking. The model, which includes an on-off type ABS controller, was developed to accurately simulate the steer, drive, and trailer axle drum (or disc) brakes on modern heavy commercial vehicles. This model includes parameters for the pneumatic brake control and operating systems, a 4s/4m (four sensor, four modulator) ABS controller for the tractor, and a 2s/2m ABS controller for the trailer. The dynamics of the pneumatic control (treadle system) are also modeled. Finally, simulation results are compared to experimental data for a variety of conditions.