Satisfaction of Modeling Requirements for Intelligent Navigation Systems: Risk Management Context

Abstract

AbstractThis work aims to boost the reliability and safety of Intelligent Transportation Systems (ITSs). To meet this goal, a particular risk assessment and management scheme is introduced to provide navigation approaches with strong safety guarantees. On the one hand, the interval analysis is adopted to develop a high fidelity model used for risk assessment purposes. This model is based on a set-membership computation of the Time-To-Collision (TTC) indicator. The TTC approximation methodology, which fits well the car-following scenario, takes into account several uncertainties of distinct sources. Even more, a novel second-order set-membership TTC formalization is introduced by solving a polynomial equation with interval coefficients. This formalization is suggested in an effort to diminish modeling errors. Both the first and second order interval-based TTC are improved via a correlation analysis-based statistical process. On the other hand, the complexity aspects of modern architectures are analyzed in this work. The tackled analysis emphasizes the destructive impacts of the inter/intra-vehicular communication on ITSs reliability. Thus, a Response Time Analysis (RTA) scheme is integrated into the proposed risk management to consider explicitly the communication latency-related material constraints. Then, the RTA results are involved into the simulation work. Finally, the simulation results applied on an adaptive cruise control system of both high/low-order TTC formalizations demonstrate that the low-order model inaccuracy is compensated. Through the interval/correlation analysis and the consideration of the material constraints, a great balance between modeling accuracy and simplicity is performed.KeywordsIntelligent vehiclesRisk managementInterval-based modelingCorrelation analysisCommunication delaysTime to collision