APACC Cross-Domain Validation Data (Automotive/Railway)
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资源简介:
Validation datasets for Artificial Precognition Adaptive Cognised Control (APACC), a neuro-symbolic MIMO control architecture for safety-critical autonomous systems (US Patent 9,645,576 B2).
Automotive domain: 10,000 trials across 8 scenario types (urban intersection, pedestrian crossing, highway merging/overtaking, emergency avoidance, adverse weather) using CARLA simulator with Honda Civic parameters. Compares APACC against PID, MPC, DRL, and Hybrid controllers. Key result: 51% reduction in peak deceleration vs PID baseline.
Railway domain: 168 hours continuous deployment on UK Network Rail infrastructure (Workington–Sellafield route, 32 km) under Government SBRI Project EDGE. Includes 6,026 telemetry records across 4 MNOs (EE, Vodafone, Three, O2) with Iridium satellite backup, plus 256 handover events. Key result: 94.9% handover prediction accuracy.
Package contains: raw trial data, MIMO telemetry, configuration files (NSSD parameters, fuzzy rulesets, full architecture specification), analysis scripts, and dataset generators for reproducibility.
Accompanies manuscripts submitted to IEEE Access and Robotics and Autonomous Systems (Elsevier).
创建时间:
2025-12-17



