A network traffic model with controlled autonomous vehicles acting as moving bottlenecks

Zhexian Li, Michael W. Levin, Raphael Stem, Xu Qu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this study, we develop a traffic model to simulate network traffic evolution under the impact of controlled autonomous vehicles acting as moving bottlenecks. We first extend the Newell-Daganzo method to track the trajectories of moving bottlenecks and calculate the cumulative number of vehicles passing moving bottlenecks. By integrating the solutions to the cumulative number of vehicles passing moving bottlenecks and link nodes as boundary conditions in the link-transmission models, we can incorporate the impact of moving bottlenecks into the flow of traffic at a network scale. The numerical simulation results demonstrate the effectiveness of the developed model to track trajectories of the moving bottlenecks and simulate their impact on freeway traffic.

Original languageEnglish (US)
Title of host publication2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728141497
DOIs
StatePublished - Sep 20 2020
Event23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020 - Rhodes, Greece
Duration: Sep 20 2020Sep 23 2020

Publication series

Name2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020

Conference

Conference23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020
Country/TerritoryGreece
CityRhodes
Period9/20/209/23/20

Bibliographical note

Funding Information:
The research of Z. Li and X. Qu was supported in part by the National Key R&D Program in China (Grant No. 2018YFB1600600) and the National Natural Science Foundation of China (Grant No.51878161).

Publisher Copyright:
© 2020 IEEE.

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