AI-Integrated Traffic Information System: A Synergistic Approach of Physics Informed Neural Network and GPT-4 for Traffic Estimation and Real-Time Assistance-Reference-Cited by-同舟云学术

AI-Integrated Traffic Information System: A Synergistic Approach of Physics Informed Neural Network and GPT-4 for Traffic Estimation and Real-Time Assistance

Published:2024 Issue: Volume:12 Page:65869-65882
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Syum Gebre Tewodros¹^ORCID,Beni Leila²^ORCID,Tsehaye Wasehun Eden¹,Elikem Dorbu Freda³^ORCID

Affiliation:

1. Applied Science and Technology Program, College of Science and Technology, North Carolina A&T State University, Greensboro, NC, USA

2. Geomatics Program, College of Science and Technology, North Carolina A&T State University, Greensboro, NC, USA

3. Department of Computational Data Science and Engineering, North Carolina A&T State University, Greensboro, NC, USA

Funder

North Carolina Department of Transportation

“NC Transportation Center of Excellence on Connected and Autonomous Vehicle Technology (NC-CAV)”

Microsoft’s Accelerate Foundation Models Academic Research Initiative

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10526250.pdf?arnumber=10526250

Reference40 articles.

1. Spatial knowledge impairment after GPS guided navigation: Eye-tracking study in a virtual town

2. A methodology to explain neural network classification

3. Traffic state estimation by backward moving observers: An application and validation under an incident

Cited by 1 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. An Integrated Framework of GPT-4 and PINN for Dynamic Traffic Estimation and Support;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07