Real-time execution of planned routes often requires re-planning, especially in dynamic, highly unpredictable environments. Ad-hoc re-planning in case of failure of an optimal (suboptimal) plan leads to deterioration of solution quality. Moreover, it becomes costly and often unmanageable under real time constraints. This paper describes an approach of a partitioning scheme for urban route planning problem domain into a hierarchy of subproblems and an algorithm for rule-based top-down route derivation. A hierarchical, rule-based approach is aimed at granular planning for generating robust, multi-variant plans.
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