RCT-AD: Reliability-Aware Context and Temporal BEV Reasoning for End-to-End Autonomous Driving
Overview
This research introduces RCT-AD, a framework designed to enhance end-to-end autonomous driving by explicitly modeling feature reliability and temporal consistency within a shared Bird's-Eye-View (BEV) representation.
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Control: reported autonomous
“RCT-AD: Reliability-Aware Context and Temporal BEV Reasoning for End-to-End Autonomous Driving”
Exact source · revision 1Source owner not reported
Reported quantity · NDS score: 61.5 other · Basis not reported
“diction, and trajectory planning. RCT-AD achieves 61.5 NDS, 52.9 mAP, and 52.3 mIoU while maintaining competitive computational efficiency. These results demonstrate the effectiveness of reliability-aware temporal BEV reasoning for unified perception, prediction, and planning.”
Exact source · revision 1Source owner not reported
Reported quantity · mAP score: 52.9 other · Basis not reported
“diction, and trajectory planning. RCT-AD achieves 61.5 NDS, 52.9 mAP, and 52.3 mIoU while maintaining competitive computational efficiency. These results demonstrate the effectiveness of reliability-aware temporal BEV reasoning for unified perception, prediction, and planning.”
Exact source · revision 1Source owner not reported
Reported quantity · mIoU score: 52.3 other · Basis not reported
“diction, and trajectory planning. RCT-AD achieves 61.5 NDS, 52.9 mAP, and 52.3 mIoU while maintaining competitive computational efficiency. These results demonstrate the effectiveness of reliability-aware temporal BEV reasoning for unified perception, prediction, and planning.”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalRCT-AD: Reliability-Aware Context and Temporal BEV Reasoning for End-to-End Autonomous Driving
This research introduces RCT-AD, a framework designed to enhance end-to-end autonomous driving by explicitly modeling feature reliability and temporal consistency within a shared Bird's-Eye-View (BEV) representation.
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