A data-driven stacking fusion approach for pedestrian trajectory prediction-Reference-Cited by-同舟云学术

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A data-driven stacking fusion approach for pedestrian trajectory prediction

Published:2022-08-01 Issue: Volume: Page:1-24
ISSN:2168-0566
Container-title:Transportmetrica B: Transport Dynamics
language:en
Short-container-title:Transportmetrica B: Transport Dynamics

Author:

Chen Hao¹,Zhang Xi²,Yang Wenyan²,Lin Yiwei²

Affiliation:

1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, People’s Republic of China

2. School of Mechanical Engineering and MoE Key Lab of Artificial Intelligence, Shanghai Jiao Tong University, Shanghai, People’s Republic of China

Funder

Key Special Projects for International Cooperation in Science and Technology Innovation

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Transportation,Modeling and Simulation,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/21680566.2022.2103050

Reference41 articles.

1. Modelling shared space users via rule-based social force model

2. A Strategic Approach to Intelligent Functions in Vehicles

3. A Situational Awareness Approach to Intelligent Vehicle Agents

Cited by 2 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. A new uncertainty processing method for trajectory prediction;Applied Intelligence;2024-06-07

2. Pedestrian lane formation with following–overtaking model and measurement of system order;Chinese Physics B;2024-01-01

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