<scp>SafeEdge</scp> : Intention‐Aware Cooperative Motion Planning for Autonomous Vehicles Over Mobile Edge Networks

ABSTRACT Autonomous vehicles often struggle in dense urban intersections because of occlusions and reactive single‐vehicle planners. SafeEdge tackles this challenge by partitioning cooperative motion planning across a three‐tier mobile‐edge hierarchy. A graph‐transformer intention generator running on roadside and metro‐edge nodes fuses V2X trajectory snippets from up to 120 agents into kilobyte‐size probability maps of future maneuvers. Each vehicle keeps feasibility checks on board, while large‐scale collision resolution is off‐loaded to a metro‐edge mixed‐integer solver. A Coq‐verified safety shield triggers emergency braking whenever network latency exceeds a derived bound. Deployed on 10 Jetson Orin NX cars and 4 Xeon Silver edge servers over a standalone 5 G link, SafeEdge clears four‐way intersections with a 96% success rate and a 95th‐percentile decision latency of 32 ms—well below the 50 ms safety envelope. Relative to an on‐board MPC baseline, emergency‐brake events drop by 70% and energy per kilometer falls by 11%. These results demonstrate that intention‐aware, edge‐partitioned planning can simultaneously satisfy real‐time and safety requirements in dense urban driving.