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The increasing numbers of paved roadways throughout the world have motivated the development of automated methods of assessing road pavement conditions. A method of developing an automated profiling vehicle that can rapidly acquire and accurately determine road roughness levels is presented. It is shown that it is important to compensate for the chassis dynamics in order to minimize the effects of suspension system interactions when computing the road roughness level. Experimental results from a prototype vehicle are detailed where the effectiveness of the vehicle design method is demonstrated.

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.