The vision of autonomous vehicles is becoming a reality. Advanced driver assistance systems have the potential to improve transportation safety and efficiency, and offer the possibility of environmental and economical gains. However, navigation and control of autonomous vehicles is an intricate task. The vehicle needs to make decisions and respond to situations on its own. Graph-search based route planning has the potential to reduce replanning times and provides the end-user with feasible and optimized plans. This thesis adopts the real-time capable, re-planning DLite algorithm as a powerful planning workhorse. The algorithm conducts graph-search on a state lattice graph, and uses motion primitives to construct a plan. The route planner inherently handles inexact motion, which lends itself well in practice as the vehicle cannot be expected to follow instructions to the letter. The route planner is able to plan in large and obstacle-laden cavelike terrains, and according to a cost map (e.g. a map pointing out fuelefficient routes), with an average re-planning time of less than 0.1 seconds. The state lattice graph is by construction feasible, which renders the planned path of the route planner physically possible for the vehicle to follow in practice. ; Autonoma fordon är en framtidsvision som aktualiseras allt mer. Avancerade förarsystem har potential att förbättra transportsäkerheten, och medför möjlighet till ekonomisk och miljömässig förbättring. Dock är navigering och kontroll av autonoma fordon en intrikat uppgift, då fordonet måste fatta beslut och hantera situationer på egen hand. Grafbaserad ruttplanering minskar omplaneringstiderna, samtidigt som den genererar genomförbara och optimerade planer. Ruttplaneraren i denna avhandling nyttjar en realtidskapabel och kraftfull omplaneringsalgoritm vid namn DLite. Algoritmen utför grafsökningar i en regelbunden grafstruktur, och använder sig av smarta rörelsesegment då den konstruerar en rutt till mål. Ruttplaneraren tar hänsyn till oprecisa fordonsrörelser, ...


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    Titel :

    Path Planning for Autonomous Heavy DutyVehicles in Unknown Environments using GraphSearch


    Beteiligte:

    Erscheinungsdatum :

    2013-01-01


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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