01764197

Component

https://annualmeeting.myt...nlineProgram/Details/15714

Distributed Fiber-Optic Sensing (DFOS) for wide-area traffic monitoring is an emerging field with far-reaching applications like congestion and trajectories detection, travel time estimation, vehicle counting etc. The most captivating aspect of DFOS is that a single sensing and processing unit can monitor traffic flow in real-time for more than 80 km while utilizing existing fiber infrastructures laid alongside roadways. This work presents a novel algorithm named TrafficNet, a deep neural network for effective extraction of traffic flow patterns using DFOS systems. Proposed TrafficNet is capable of denoising DFOS data and identifying the essential components corresponding to each traversing vehicle. TrafficNet is the first of its kind neural network developed to monitor traffic by detecting vehicle trajectories and estimating various traffic flow properties using DFOS. Experimental results indicate that TrafficNet achieves 96% accuracy for estimation of average traffic speeds as compared to existing inductive loop detectors.

This paper was sponsored by TRB committee AED50 Standing Committee on Artificial Intelligence and Advanced Computing Applications.

TRBAM-21-01128

English

13p

2021

Transportation Research Board 100th Annual Meeting

Digital/other

Figures; Maps; References (20) ; Tables

Fiber optics; Neural networks; Remote sensing; Traffic flow; Traffic speed measurement; Traffic surveillance; Vehicle trajectories; Video imaging detectors

Highways; Operations and Traffic Management; Safety and Human Factors

Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-01128

TRIS, TRB, ATRI

Dec 23 2020 11:22AM