Abstract
Vehicular safety functions that intervene in dangerous driving situations increase automotive safety. As such functions use the measurements of sensors in order to interpret the driving situation, unavoidable sensor measurement errors have a negative impact on both the safety and the satisfaction of the customer. In this paper, a new methodology for the robust design of an automatic emergency braking (AEB) system considering sensor measurement errors is proposed. Based on a stochastic model, the robust design is formulated as an optimization problem, whose solution results in the optimal values for the parameters of the AEB system, i.e., of both the sensor and the function it is based on, with respect to a probabilistic quality measure. Besides this joint function and sensor design, the robust sensor design for a given function and the robust function design for a given sensor considering sensor measurement errors in case of the AEB system are formulated as optimization problems using the same probabilistic quality measure. An expression for this probabilistic quality measure is derived, and the elaborated theoretical results are illustrated and verified by numerical examples. Moreover, the new design methodology provides the designer with a design space for choosing the parameter values.
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