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This paper is directed to an Enhanced Traction Stability Control System (ETSC) that is based on the estimate of vehicle yaw rate and does not require yaw rate or lateral accelerometer sensors information. The validity of the yaw rate estimate is determined and used to select the appropriate control methodology. We estimate the vehicle yaw rate based on the measured speeds of the un-driven wheels of the vehicle, and we utilize various other conditions to determine if the estimated yaw rate is valid for control purposes. When it is determined that the yaw rate is valid, a combined closed-loop yaw rate feedback, and an open-loop feed-forward derivative control based on the driver input is employed. Whereas in conditions under which it is determined that the estimated yaw rate is not valid, an open-loop feed-forward control with a proportional, derivative and a diminishing integrator terms, is employed. In addition, we develop a bank angle compensation algorithm using the steering angle, vehicle speed, and the estimated yaw rate to compensate for the effect of banked road. Test results indicate marked enhancement of vehicle stability with ETSC when compared with ABS and TCS. Finally, we present test results to compare the performance of ETSC system to yaw rate feedback control only Electronic Stability Control System (ESC) using yaw rate and lateral accelerometer sensors information.

Active Front Steering (AFS) systems have recently been introduced for passenger vehicles to improve handling stability under adverse road. conditions. AFS provides a mechanism to augment the steering angle with a small displacement actuator. In this configuration, the steering angle of the front wheels is the combined input of the handwheel with an additional small angle component from an electronically controlled actuator. This paper investigates AFS for large trucks to assist in avoiding jackknife conditions. Emphasis is given to design aspects to minimize the tendency of AFS systems to interfere with the driver's perception of the vehicle responsiveness.

The authors have developed a steering entropy method to easily and accurately quantify the workload imposed on drivers who are engaged in activities apart from the normal driving operations of longitudinal and lateral control. A driver's steering behavior tends to become more discontinuous while performing an activity in addition to driving. To quantify these discontinuities, steering entropy values are obtained from a time-series history of steering angle data. A special-purpose driving simulator and a test procedure have been developed that allow workload evaluations to be conducted efficiently. The simulator and test procedure were used to evaluate the additional workload incurred by 14 different types of activities. The steering entropy results were compared with a dual task method as well as a subjective evaluation method. These results showed a high degree of correlation between the three approaches, which confirmed the validity of the steering entropy method as a means to quantify workload. Measurements were then made of progressively more difficult tasks. It was found that the steering entropy values increased in direct proportion to the degree of (subjective) task difficulty, which corroborated the high measurement accuracy of this method.