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Monte Carlo simulation is used to determine the likelihoods of competing scenarios offered by opposing parties involved in a motor vehicle accident. A case study is presented in which there is a dispute among the parties about who passed who first. It is shown that even though both scenarios are possible, one of the scenarios has a much greater likelihood. Besides demonstrating how Monte Carlo simulation provides probability information that can be used to weigh the likelihood of competing scenarios, the case study also provides another example of how Monte Carlo simulation can dig information out of the evidence surrounding an accident that cannot be obtained by other methods.

This paper presents an optimal control strategy for assigning wheel slips on all of the wheels of a tractor/trailer combination. Most ABS controllers work on a wheel by wheel or an axle by axle basis without consideration for overall system stability. This controller is based on a linear program (LP) and assigns wheel slips for each wheel in accordance with one of the following criteria: 1) During an emergency braking maneuver, optimal wheel slips are determined which maximize stopping while constraining the system to be stable, or 2) During a nonemergency braking maneuver, the controller is used to maximize stability while maintaining an achievable (commanded) deceleration. Computer simulations, which modeled a full tanker truck, were run to compare the response of the proposed controller with two controllers which incorporated select-low control and individual control ABS systems on various axles.

This paper studies the performance benefits attainable by application of an advanced brake controller. This brake controller is optimal in the sense that it determines the wheel slips that provide the maximum level of deceleration while maintaining a specified level of directional stability. It determines target wheel slips for each wheel individually. The performance of the controller is compared to the performance of a more restricted controller that determines only one target wheel slip for the front tires and only one target wheel slip for the rear tires.

This paper considers robust controller design applied to a backward steering system for tow-vehicle/trailer combinations. An Inverse Linear Quadratic Regulator (ILQR) approach is followed. It combines pole assignment methods with conventional LQ problem. It overcomes two problems associated with these separate methods. It overcomes the robustness problems of pole placement methods, and overcomes the trial and error required in the LQR method. A Kalman observer is used, but is modified by using the loop transfer recovery (LTR) technique. The combination of the robust LQ problem and robust filter is called a ILQG/LTR controller. The proposed controller is applied to both 2WS and 4WS tow-vehicle and shows significantly more robust performance than previous controllers. Moreover, employing a 4WS tow-vehicle significantly expands the range and effectiveness of the control.

An electromagnetic brake retarder is a device for assisting the brakes of heavy vehicles during descents down long steep inclines. As it operates, a brake retarder heats up and this causes its performance to deteriorate. The retarding force a brake retarder can develop can drop by over 50% as it heats up, and this can lead to a possible “run-away” of the vehicle on which it is installed. Because of this temperature dependency the control of a brake retarder involves two objectives; the first is to maintain the desired vehicle speed and the second is to prevent the retarder from overheating. This paper determines the optimal control of the brake retarder by using dynamic programming.

A set of rules is derived that can be used to determine effective choices for the wheel slips to be maintained at the wheels of a vehicle that has the capability to control its wheel slip levels. The determined wheel slips will be effective at enhancing the stability of the vehicle.

This paper examines how a human torso rebounds from seats in low to moderate speed collisions. A torso model and a seat model are combined and numerical integration is used to predict the response characteristics.