Reachability Estimation in Dynamic Driving Scenes for Autonomous Vehicles

Autonomous vehicles will find an infinite number of possible scenarios while driving in urban environments and need to react in a proper manner. For that reason, it is important to have algorithms that can propose driving alternatives for different type of scenarios in a global and unified way instead of using rule-based algorithms which depend on the driving scene. This paper presents a reachability estimation algorithm designed to obtain a safe and comfort-optimized trajectory set for different driving scenarios. First, a finite number of path candidates are created using Bezier curves. Then, all valid path ´ candidates are combined with the reachable sets of dynamic obstacles to generate speed profiles consistent with safety and comfort requirements. The output of this algorithm would allow a decision-making strategy to select the optimum candidate depending on different criteria.This work has been partially funded by the Spanish Ministry of Science, Innovation and Universities with National Project COGDRIVE (DPI2017- 86915-C3-1-R), the Community of Madrid through SEGVAUTO 4.0-CM (S2018-EMT-4362) Programme, and by the European Commission through the Projects PRYSTINE (ECSEL-783190-2) and SECREDAS (ECSEL783119-2).Peer reviewe