摘要：AbstractSeveral risk management strategies are integrated into today’s intelligent vehicles to guarantee safety. To be efficient, these strategies must handle the uncertainty propagation into the navigation process. For a more reliable risk management, this work presents a novel set-membership over-approximation of the Time-To-Collision (TTC), which fits a vehicle following scenario. The interval analysis is used to consider different uncertainty sources with respects to surrounding measurement conditions. For optimization aims, statistical properties of the measurements, which are based on the correlation evolution, are employed to avoid conservative results. It is assumed that the vehicle dynamics and correspondingly the correlation between measurements cannot drastically change in a short time horizon. Accordingly, the amount of uncertainty assigned to each measurement, evaluated per interval, is decreased. This fact prohibits irregularities in the correlation relating variables. The proposed risk management approach is integrated into the architecture of an Adaptive Cruise Control (ACC). Simulation results prove the overall risk management efficiency and its ability to handle uncertainties.
关键词：KeywordsIntelligent transportation systemsrisk managementtime to collisioninterval analysiscorrelationuncertaintyadaptive cruise control
