Learning Traffic Flow Dynamics Using Random Fields
This paper presents a mesoscopic traffic flow model that explicitly describes the spatio-temporal evolution of the probability distributions of vehicle trajectories. The dynamics are represented by a sequence of factor graphs, which enable learning of traffic dynamics from limited Lagrangian measure...
Main Authors: | Saif Eddin G. Jabari, Deepthi Mary Dilip, Dianchao Lin, Bilal Thonnam Thodi |
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Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8835040/ |
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