The University of Southampton
University of Southampton Institutional Repository

Developing and evaluating a coordinated person-based signal control paradigm in a corridor network

Developing and evaluating a coordinated person-based signal control paradigm in a corridor network
Developing and evaluating a coordinated person-based signal control paradigm in a corridor network
Connected Vehicles (CVs) provide both vehicle trajectory data and occupancy information to the junction controller, which make person-based signal controls to be possible by realizing the importance of reducing person delay. This study presents a coordinated person-based signal control algorithm (C-PBC), which has extended a previously developed approach from isolated junctions to multiple junctions. C-PBC incorporates vehicle information that is outside the CV communication range from the adjacent junction. It also updates data inputs for signal optimization algorithms based on formulated different arrival vehicle trajectory situations and coordinated data supplement algorithms. The developed algorithm has been evaluated using simulation with benchmarking signal control methods under a variety of scenarios involving CV penetration rates and predictive horizons. The results indicate that C-PBC is able to significantly improve person delay reduction when compared with fixed time control and vehicle-based control using CV data in 100% CV penetration rate under saturated flow conditions.
C-PBC, Traffic signal control, connected vehicle, coordinated control, person-based control
1029-0354
498-523
Wu, Zongyuan
f1cb0318-5bf0-465d-8454-65d63495491f
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Anvari, Bani
f94e2ccb-1d88-4980-8d29-f4281995d072
Wu, Zongyuan
f1cb0318-5bf0-465d-8454-65d63495491f
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Anvari, Bani
f94e2ccb-1d88-4980-8d29-f4281995d072

Wu, Zongyuan, Waterson, Ben and Anvari, Bani (2022) Developing and evaluating a coordinated person-based signal control paradigm in a corridor network. Transportation Planning and Technology, 45 (6), 498-523. (doi:10.1080/03081060.2022.2134128).

Record type: Article

Abstract

Connected Vehicles (CVs) provide both vehicle trajectory data and occupancy information to the junction controller, which make person-based signal controls to be possible by realizing the importance of reducing person delay. This study presents a coordinated person-based signal control algorithm (C-PBC), which has extended a previously developed approach from isolated junctions to multiple junctions. C-PBC incorporates vehicle information that is outside the CV communication range from the adjacent junction. It also updates data inputs for signal optimization algorithms based on formulated different arrival vehicle trajectory situations and coordinated data supplement algorithms. The developed algorithm has been evaluated using simulation with benchmarking signal control methods under a variety of scenarios involving CV penetration rates and predictive horizons. The results indicate that C-PBC is able to significantly improve person delay reduction when compared with fixed time control and vehicle-based control using CV data in 100% CV penetration rate under saturated flow conditions.

Text
Evaluating_coordinated_person_based_signal_control _paradigm - Version of Record
Download (4MB)

More information

Accepted/In Press date: 3 October 2022
Published date: 18 October 2022
Additional Information: Publisher Copyright: © 2022 Informa UK Limited, trading as Taylor & Francis Group.
Keywords: C-PBC, Traffic signal control, connected vehicle, coordinated control, person-based control

Identifiers

Local EPrints ID: 478611
URI: http://eprints.soton.ac.uk/id/eprint/478611
ISSN: 1029-0354
PURE UUID: 01e33a94-72fc-46d0-a3e4-1174a2745fe9
ORCID for Ben Waterson: ORCID iD orcid.org/0000-0001-9817-7119
ORCID for Bani Anvari: ORCID iD orcid.org/0000-0001-7916-7636

Catalogue record

Date deposited: 05 Jul 2023 17:33
Last modified: 17 Mar 2024 02:46

Export record

Altmetrics

Contributors

Author: Zongyuan Wu
Author: Ben Waterson ORCID iD
Author: Bani Anvari ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×