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Physics-Aware Learning-Based Vehicle Trajectory Prediction of Congested Traffic in a Connected Vehicle Environment

Journal Article · · IEEE Transactions on Vehicular Technology
 [1];  [2];  [3]
  1. Department of Civil and Environmental Engineering, University of South Florida, Tampa, FL, USA; OSTI
  2. Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, USA
  3. Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA

Not provided.

Research Organization:
Univ. of South Florida, Tampa, FL (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
EE0009658
OSTI ID:
2418090
Journal Information:
IEEE Transactions on Vehicular Technology, Journal Name: IEEE Transactions on Vehicular Technology Journal Issue: 1 Vol. 72; ISSN 0018-9545
Publisher:
IEEE
Country of Publication:
United States
Language:
English

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A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method journal December 2017
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Interactive Trajectory Prediction of Surrounding Road Users for Autonomous Driving Using Structural-LSTM Network journal November 2020
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Long Short-Term Memory-Based Human-Driven Vehicle Longitudinal Trajectory Prediction in a Connected and Autonomous Vehicle Environment journal February 2021
Car-Following Described by Blending Data-Driven and Analytical Models: A Gaussian Process Regression Approach
  • Soldevila, Ignasi Echaniz; Knoop, Victor L.; Hoogendoorn, Serge
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2675, Issue 12 https://doi.org/10.1177/03611981211032648
journal July 2021

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