Control of Networked Traffic Flow Distribution: A Stochastic Distribution System Perspective

Stanley Young, Hong Wang, H. M. Abdul Aziz, Sagar Patil

Research output: Contribution to conferencePaperpeer-review

Abstract

At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections. In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic modelling and control for a one-way single-lane corridor traffic system based on theory of stochastic distribution control that shapes the PDF of the queue length.

Original languageAmerican English
DOIs
StatePublished - 17 Oct 2017
Event1st International Conference on Internet of Things and Machine Learning, IML 2017 - Liverpool, United Kingdom
Duration: 17 Oct 201718 Oct 2017

Conference

Conference1st International Conference on Internet of Things and Machine Learning, IML 2017
Country/TerritoryUnited Kingdom
CityLiverpool
Period17/10/1718/10/17

Bibliographical note

Publisher Copyright:
© 2017 Association for Computing Machinery.

NREL Publication Number

  • NREL/CP-5400-71863

Other Report Number

  • Article No. 37

Keywords

  • Stochastic distribution control
  • Traffic queueing modelling

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