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A novel speed and position dependent Lane Keeping Assistance (LKA) control strategy for heavy vehicles is proposed. This LKA system can be implemented with any torque overlay system capable of accepting external position or torque commands. The proposed algorithm tackles the problem of lane keeping in two ways from a heavy vehicle's perspective. First, it stabilizes the vehicle's lateral position by bringing it to the center of the lane and giving it the correct heading to stay there. This is done using a speed and position dependent control strategy that becomes less aggressive as the vehicle's speed increases and as it gets closer to the center of the lane. Such speed and position dependency is especially critical in heavy vehicles where unnecessary aggressive control can lead to oscillations about the lane's centerline when cruising at high speeds.

This paper reviews activities relating to understanding, and improving the on-center performance of heavy truck steering systems. Initially, the on-center steering performance characteristics for commercial vehicles were quantified. Steering wheel torque and angular position were the prime measurables. Graphical analyses of the on-center handling data were performed. To better understand the data, and to insure statistical significance, an algebraic model of the analyzed data was developed, with confidence intervals determined. The calculated system stiffness, as determined from the steering wheel data, was found to be a key discriminator between steering gears. System stiffness is a function of several component values, which were measured in the laboratory. Finally, to test the above findings, a correlation study of subjective driver impressions with measured steering gear characteristics and objective vehicle measures was performed.

Commercial vehicles must transport an increasing volume of freight on a relatively fixed infrastructure. Some of these vehicles are highly specialized and customized to perform particular tasks. One way to increase freight hauling efficiency is to allow longer vehicles with more axles. These vehicles will have different handling properties and must be driven on existing infrastructure. Longer term, autonomous-like vehicles could be used to increase vehicle utilization. In both cases characterizations of multi-axle vehicle dynamics are required. A two-dimensional yaw plane model is used in practice to analyze handling performance of two-axle passenger cars. Commonly known as the "bicycle" model because it combines all tire forces associated with a given axle to act on the centerline of the vehicle, the yaw plane model allows lateral velocity and yaw rate degrees of freedom.