A Personalized Deep Learning Approach for Trajectory Prediction of Connected Vehicles

Keyphrases

• Time Series Modeling 100%
• Deep Learning Methods 100%
• Connected Vehicles 100%
• Trajectory Prediction 100%
• Driving Style 80%
• Leading Vehicle 80%
• Modeling Approach 40%
• Gaussian Mixture Model 40%
• Time Headway 40%
• Space Headway 40%
• Front Vehicles 40%
• Modeling Method 20%
• Human Being 20%
• Jerk 20%
• Problem-based 20%
• Vehicle Speed 20%
• Fully Connected 20%
• Simulation Data 20%
• Vehicle-based 20%
• Connected Autonomous Vehicles 20%
• Long Short-term Memory 20%
• Long Short-term Memory Neural Network 20%
• Communication Signal 20%
• Next Generation Simulation (NGSIM) 20%
• Following Vehicle 20%
• Recurrent Neural Network Model 20%
• Inter-vehicle Communication 20%
• Vehicle Trajectory Prediction 20%
• Storage Layer 20%
• Vehicle Behavior 20%
• Personalized Trajectory 20%
• Unsupervised Clustering 20%
• Vehicle Analysis 20%
• Leading-following 20%

Computer Science

• Deep Learning Method 100%
• Learning Approach 100%
• Leading Vehicle 100%
• Long Short-Term Memory Network 50%
• Gaussian Mixture Model 50%
• Autonomous Vehicles 25%
• Neural Network Model 25%
• Recurrent Neural Network 25%
• Data Simulation 25%
• Unsupervised Clustering 25%

Engineering

• Learning Approach 100%
• Joints (Structural Components) 100%
• Deep Learning Method 100%
• Leading Vehicle 80%
• Gaussian Mixture Model 40%
• Long Short-Term Memory 40%
• Network Model 20%
• Recurrent Neural Network 20%