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This paper is an extension to the work presented in part I [1]. The control objective is still the same - use a logic based control design technique to assign a wheel slip, λ, to each corner of a vehicle, to track overall desired vehicle dynamics. As in part I, a fuzzy logic based controller is the primary control, with additional logic to select the inside/outside classifiers for the wheels. In part I, only the reduction of yaw rate error, e, was considered. It was shown that, although the overall system had satisfactory performance, there was slight deteriorization in the tracking performance when trying to compensate through a significant vehicle sideslip angle, β. In this paper, additional logic is introduced into the control to limit the vehicle sideslip angle, β; thus, allowing for a more robust desired yaw rate, Ωd, tracking control performance. The emergency lane change maneuver is simulated to show the effectiveness of the redesigned control.

It is estimated that in the United States, nearly one quarter of all fatal automobile accidents involve a vehicle rollover. [1] In order to reduce fatalities and serious injuries, it is desirable to develop a sensing system that can detect an imminent rollover condition with sufficient time to activate occupant safety protection devices. The goals of a Rollover Sensing Module (RSM) are; 1 To accurately estimate vehicle roll and pitch angles 2 To reliably predict in a timely manner an imminent rollover 3 To eliminate false activation of safety devices 4 To function properly during airborne conditions 5 To be as autonomous as possible, not requiring information from other vehicle subsystems.

Many vehicle-dynamics models exist to study the motion of a vehicle. Most of these models fall into one of two categories: very simple models for basic analyses and high-order models consisting of many degrees-of-freedom. For many scenarios, the simple models are not adequate. At the same time, for many vehicle handling and braking studies, the high-order models are more complex than necessary. This paper presents a model that includes the dynamics that are relevant to studying vehicle handling and braking, but is still simple enough to run in near real-time. The model was implemented in such a way that it is easily customized for a particular study. Predictions from this simplified model were compared against a high-order model and against actual vehicle test data. The simulations indicate a close agreement in the results.

This paper investigates a method for improving vehicle stability by incorporating feedback from a yaw rate sensor into an electric power steering system. Presently, vehicle stability enhancement techniques are an extension of antilock braking systems in aiding the driver during vehicle maneuvers. One of the contributors to loss of vehicle control is the reduction in tactile feedback from the steering handwheel when driving on wet or icy pavement. This paper presents research indicating that the use yaw rate feedback improves vehicle stability by increasing the amount of tactile feedback when driving under adverse road conditions.

An algorithm for estimation of vehicle yaw rate and side slip angle using steering wheel angle, wheel speed, and lateral acceleration sensors is proposed. It is intended for application in vehicle stability enhancement systems, which use controlled brakes or steering. The algorithm first generates two initial estimates of yaw rate from wheel speeds and from lateral acceleration. A new estimate is subsequently calculated as a weighted average of the two initial ones, with the weights proportional to confidence levels in each estimate. This preliminary estimate is fed into a closed loop nonlinear observer, which generates the final estimate of yaw rate along with estimates of lateral velocity and side slip angle. Parameters of the observer depend on the estimated surface coefficient of adhesion, thus providing adaptation to changes in road surface coefficient of adhesion.

The purpose of this paper is to investigate occupant injuries which may be sustained during a single-event crash with known roll mechanism. The data was obtained from the weighted National Automotive Sampling System/ Crashworthiness Data System (NASS-CDS) for calendar years 1992 to 1996. The effect of number of rollover turns, roll direction, ejection and belt usage on driver injury responses was analyzed in single-event trip-overs. Trip-overs were chosen for the analysis because they account for over 50% of rollover crashes. The number of rollovers was divided in 3 categories: ¼ to ½ turn, ¾ to 1 turn and above 1 turn. Roll direction was either roll-left or a rollright along the longitudinal axis of the vehicle. Roll-left represents a roll with the driver side leading, while a roll right is with the right front passenger side leading. In the database used in this study, there were three times more belted drivers than unbelted.