Using a Diffusion Model for Pedestrian Trajectory Prediction in Semi-Open Autonomous Driving Environments
Author:
Affiliation:
1. National Engineering Laboratory for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China
Funder
Major Special Projects in Zhengzhou
Development of Critical Technologies
Multi-Scenario Demonstration for Autonomous Driving Vehicles
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/7361/10530892/10489838.pdf?arnumber=10489838
Reference44 articles.
1. Set-Based Prediction of Traffic Participants Considering Occlusions and Traffic Rules
2. Deep Reinforcement Learning based Energy-efficient Decision-making for Autonomous Electric Vehicle in Dynamic Traffic Environments
3. Vehicle Trajectory Prediction by Integrating Physics- and Maneuver-Based Approaches Using Interactive Multiple Models
4. Pedestrian path prediction based on body language and action classification
5. Vision-Based Real-Time Online Vulnerable Traffic Participants Trajectory Prediction for Autonomous Vehicle
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