2018 · 17 citations · 1 references
ComputingCloud ComputingComputer ScienceArtificial IntelligenceAutonomous VehiclesMachine LearningDeep LearningIntelligent Transportation SystemsTraffic SafetyVehicle Communication NetworksVehicle-to-everything CommunicationDeep Learning DetectionDeep Learning-based DetectionDetection SensorsPlatform Service ArchitectureResponse TimeTraffic Accident AnalysisTraffic Accident DetectionWeb Service Architecture
This paper proposes a deep learning based Internet of vehicles system, which consists of an in-vehicle infotainment telematics platform with collisions detection sensors, a cloud based deep learning training server, and a web-based service platform. The proposed system implements deep learning based techniques to achieve traffic accident collisions detection and to provide related emergency announcement. As a result, the experimental result showed that the accuracy of traffic accident collisions detection can be achieved up to 96% and the average response time for related emergency announcement is approximately 7 seconds.
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