Real-Time Joint Estimation of Traffic States and Parameters Using Cell Transmission Model and Considering Capacity Drop

Yue Zhou, Edward Chung, Michael E. Cholette, Ashish Bhaskar

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

This paper contributes to an understudied category of traffic state estimation approaches, i.e. using a Godunov-type discrete traffic flow model (e.g. the Cell Transmission Model, CTM) to simultaneously estimate traffic flow parameters and traffic densities. Our main estimation algorithm is based on the CTM and the extended Kalman filter (EKF). Compared to previous studies, this study has two features. First, we take into account the effect of capacity drop, a factor that is largely ignored by previous studies in traffic state estimation. Second, a separate, supervisory observer capturing the capacity drop mode is attached to the main algorithm. Such a treatment enables the main estimation algorithm to more accurately switch between functions of free-flow regime and congested regime. It thus avoids mismatches between the applied models and the measurements, a common pitfall in conventional CTM-EKF approaches, hence can potentially enhance the quality of estimation. The proposed method was tested using micro-simulation data and showed a satisfactory performance in tracking variations of traffic flow parameters and estimating traffic densities in real time.

Original languageEnglish
Title of host publication2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2797-2804
Number of pages8
ISBN (Electronic)9781728103235
DOIs
Publication statusPublished - 7 Dec 2018
Event21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 - Maui, United States
Duration: 4 Nov 20187 Nov 2018

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2018-November

Conference

Conference21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
CountryUnited States
CityMaui
Period4/11/187/11/18

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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