LiveMap: Real-time dynamic map in automotive edge computing

Keyphrases

• Adaptive Offloading 50%
• Automotive Edge Computing 100%
• Autonomous Driving 50%
• Average Latency 50%
• Baseline Solution 50%
• Connected Vehicles 100%
• Control Plane 50%
• Crowdsourced Data 50%
• Deep Reinforcement Learning (deep RL) 50%
• Diverse Environment 50%
• Driving Safety 50%
• Dynamic Map 100%
• Dynamic Networking 50%
• Edge Computing Network 50%
• Extreme Weather 50%
• Feature Extraction 50%
• Individual Vehicle 50%
• Intelligent Vehicle 50%
• Large-scale Networks 50%
• Latency 50%
• Line-of-sight 50%
• Multiple Vehicles 50%
• Network Simulator 50%
• Object Combination 50%
• Object Detection 50%
• Object Matching 50%
• Offloading Algorithms 50%
• Perception Data 100%
• Projection Feature 50%
• Real-time Dynamics 100%
• Reinforcement Learning Algorithm 50%
• Scheduling Algorithm 50%
• Uncertain Environment 50%
• Vehicle Data 50%
• Vehicle Scheduling 50%
• Vehicle-based 50%
• Visual Occlusion 50%
• Wirelessly 50%

Computer Science

• Autonomous Driving 50%
• Average Latency 50%
• Control Plane 50%
• Deep Reinforcement Learning 50%
• Edge Computing 100%
• Feature Extraction 50%
• Learning Technique 50%
• Network Simulator 50%
• Object Detection 50%
• Testbed 50%