Driver Monitoring-Based Lane-Change Prediction: A Personalized Federated Learning Framework-Reference-Cited by-同舟云学术

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Driver Monitoring-Based Lane-Change Prediction: A Personalized Federated Learning Framework

Published:2023-06-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Intelligent Vehicles Symposium (IV)
language:
Short-container-title:

Author:

Du Runjia¹,Han Kyungtae²,Gupta Rohit²,Chen Sikai³,Labi Samuel¹,Wang Ziran¹

Affiliation:

1. Purdue University,College of Engineering,West Lafayette,IN 47907

2. Toyota Motor North America,InfoTech Labs,Mountain View,CA 94043

3. University of Wisconsin-Madison,College of Engineering,Madison,WI 53706

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10186382/10186383/10186757.pdf?arnumber=10186757

Reference32 articles.

1. In-Cabin Commuter Exposure to Ultrafine Particles on Los Angeles Freeways

2. Driver Head Movements in Left Outside Mirror Viewing

3. Digital Twin Simulation of Connected and Automated Vehicles with the Unity Game Engine

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. Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system;Transportation Research Part C: Emerging Technologies;2024-03

2. Privacy-Preserving Federated Class-Incremental Learning;IEEE Transactions on Machine Learning in Communications and Networking;2024

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