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The objective of this paper is to describe a Class 8 heavy truck that the Virginia Tech Center for Transportation Research has modified and instrumented for use in evaluating Intelligent Transportation Systems (ITS) technologies. The truck is capable of recording a variety of data, both electronic and video, in real-time from a suite of sensors and cameras that have been inconspicuously mounted on the tractor. The tractor, trailer, and instrumentation package enable Virginia Tech to conduct commercial vehicle ITS research related to safety and human factors, and advanced vehicle control systems (AVCS). This paper will describe the instrumentation package, and address both general and specific types of research that can be performed using this truck.

The primary purpose of this paper is to evaluate how various time-domain system identification techniques, which have been successfully used for different dynamic systems, can be applied for identifying heavy truck dynamics. System identification is the process by which a model is constructed from prior knowledge of a system and a series of experimental data. The parameters obtained from the identification process can be used for developing or improving the mathematical representation of a physical system. In contrast to lighter vehicles, heavy trucks have considerably more flexible frames. The frame can exhibit beaming dynamics in a frequency range that is within the range of interest for evaluating the ride and handling aspects of the truck. Understanding the dynamic contributions of the truck frame is essential for improving the ride characteristics of a vehicle. This understanding is also needed for designing new frame configurations for the existing or new production trucks.

Dynamic “Game Theory” brings together different features that are keys to many situations in control design: optimization behavior, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In previous studies, it was shown that vehicle stability can be represented by a cooperative dynamic/difference game such that its two agents (players), namely, the driver and the vehicle stability controller (VSC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the VSC command is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degree of freedom (DOF) vehicle handling performance model is put into discrete form to develop the game equations of motion. This study focus on the uncertainty in the inputs, and more specifically, the driver's steering input.