Collision analysis often assumes emergency deceleration begins immediately upon completion of the vehicle's mechanical brake lag. The goal of this study is to determine the driver-related delay from initial brake application to various degrees of deceleration in a simulated emergency and to test variables contributing to the modulation of driver braking. Using the data of Mazzae et al (2003), in which drivers respond to a lateral vehicle incursion, we have assessed the contribution of Time-to-Intersection (TTI), road condition, gender and crash outcome on driver emergency brake response. In the first 0.3 second phase after initial brake application, vehicle behavior was similar across all variables as drivers reached only moderate levels of deceleration. In the second phase, drivers often took more than one second to reach emergency decelerations, especially with a longer TTI. Pavement condition, gender and crash outcome were not significant factors. We discuss the consequences of driver braking behavior in the context of driver feedback and accident reconstruction analyses.

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The advantages of combining a conventional controller and a knowledge-based approach are ad dressed in the specific context of regulating a robotic manipulator with deployable and slewing links. A hierarchical structure having a high-speed crisp-algorithmic controller at the bottom layer and an intelligent tuner at an upper layer is developed. The top-level intelligent tuner uses a valid set of linguistic rules for adjusting proportional-integral-derivative servos, based on the theory of fuzzy logic. The behavior of the system is evaluated on the basis of the numerical simulation results as well as experiments with a prototype manipulator system. Results suggest significant improvement in the system performance through the fuzzy logic-based hierarchical control structure.