WZPlanner: Safe End-to-End Path Planning for Autonomous Driving in Work Zones
Bridging the gap between static map data and dynamic construction zone navigation for safer autonomous driving.
Work zones alter lane geometry through temporary traffic controls and closures that may be absent from on-board maps, challenging autonomous vehicle (AV) perception and planning. Generalization is also limited by scarce public datasets with structured geometric supervision. We pr...
ArXiv CS.CV
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WZPlanner bridges a critical safety gap by enabling autonomous vehicles to navigate unstructured and dynamic work zone environments where high-definition map data is often obsolete. By introducing advanced geometric supervision, this research significantly improves the robustness of path planning in complex, real-world road construction scenarios.
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