Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction

Author:

Hu Yeping1ORCID,Zhan Wei1ORCID,Tomizuka Masayoshi1ORCID

Affiliation:

1. Department of Mechanical Engineering, University of California, Berkeley, CA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MTP-GO: Graph-Based Probabilistic Multi-Agent Trajectory Prediction With Neural ODEs;IEEE Transactions on Intelligent Vehicles;2023-09

2. Graph Structure-Based Implicit Risk Reasoning for Long-Tail Scenarios of Automated Driving;2023 4th International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE);2023-08-25

3. Passing‐yielding intention estimation during lane change conflict: A semantic‐based Bayesian inference method;IET Intelligent Transport Systems;2023-08-09

4. Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04

5. Knowledge Distillation on Driving Intention Generator: Learn Human-like Semantic Reasoning;2023 IEEE International Conference on Real-time Computing and Robotics (RCAR);2023-07-17

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