A Stochastic Reachable Set Trajectory Prediction Modeling Method for Following Operation of Urban Rail Trains-Reference-Cited by-同舟云学术

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A Stochastic Reachable Set Trajectory Prediction Modeling Method for Following Operation of Urban Rail Trains

Published:2023-09-24 Issue: Volume: Page:3724-3729
ISSN:
Container-title:2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
language:
Short-container-title:

Author:

Yang Min¹,Lv Jidong¹,Luo Zhengwei¹,Liu Hongjie¹,Chai Ming¹,Zhang Lei²

Affiliation:

1. Beijing Jiaotong University,National Engineering Research Center of Rail Transportation Operation and Control System,Beijing,China

2. Traffic Control Technology Co., Ltd,Beijing,China

Funder

National Natural Science Foundation of China

Beijing Municipal Natural Science Foundation

China Academy of Railway Sciences Group Co., Ltd.

Foundation of China State Railway Group Co., Ltd.

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10420842/10420843/10422301.pdf?arnumber=10422301

Reference12 articles.

1. Data-driven models for train control dynamics in high-speed railways: LAG-LSTM for train trajectory prediction

2. Toward the Trajectory Predictor for Automatic Train Operation System Using CNN–LSTM Network

3. A hybrid stochastic approach for offline train trajectory reconstruction

4. A survey on motion prediction and risk assessment for intelligent vehicles

5. Simultaneous Trajectory Planning and Tracking Using an MPC Method for Cyber-Physical Systems: A Case Study of Obstacle Avoidance for an Intelligent Vehicle

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