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Exploring person-based signal control paradigms in urban road networks

Exploring person-based signal control paradigms in urban road networks
Exploring person-based signal control paradigms in urban road networks
Connected vehicle technology can provide traffic signal controllers with abundant types of data resources, e.g., vehicle occupancy data, etc. The provided data can be used to improve the performance of signal control methods and enable conversion from vehicle-based controls to person-based controls, which focus on optimizing person-related objective values, such as minimising average person delay. However, so far research in relevant fields has not fully exploited potential paradigms and benefits of person-based controls. In respect of such, this study has provided a better understanding about the impacts of occupancy information collected from connected vehicles (CVs) on urban signal controls and potential benefits to person-related performance that those information can bring. The contributions of this study include: 1) development of a three-layered DP person-based signal control mechanism (PerSiCon-Junction) in a fully CV environment at an isolated junction with a signal phase transition exploration mechanism and car-following updating theories; 2) development of a person-based control mechanism (PerSiCon-Bus) with completely flexible signal plans to apply the PerSiCon-Junction to more complex vehicle mixtures of cars and buses in a generalized 8-phases options junction; 3) proposal of a coordinated paradigm PerSiCon-Network to better understand how PerSiCon-Bus with flexible phase combinations and stage sequences should be implemented in multiple junctions; 4) realistic case and scenarios studies that assess the performance of the proposed method against benchmarking models involving vehicle-based controls using CV data; and 5) proposal of a EUVO algorithm to estimate status of unequipped vehicles with occupancy so as to improve the behaviour of PerSiCon-Network under imperfect CV penetration rate environments.
University of Southampton
Wu, Zongyuan
f1cb0318-5bf0-465d-8454-65d63495491f
Wu, Zongyuan
f1cb0318-5bf0-465d-8454-65d63495491f
Waterson, Benedict
60a59616-54f7-4c31-920d-975583953286

Wu, Zongyuan (2023) Exploring person-based signal control paradigms in urban road networks. University of Southampton, Doctoral Thesis, 290pp.

Record type: Thesis (Doctoral)

Abstract

Connected vehicle technology can provide traffic signal controllers with abundant types of data resources, e.g., vehicle occupancy data, etc. The provided data can be used to improve the performance of signal control methods and enable conversion from vehicle-based controls to person-based controls, which focus on optimizing person-related objective values, such as minimising average person delay. However, so far research in relevant fields has not fully exploited potential paradigms and benefits of person-based controls. In respect of such, this study has provided a better understanding about the impacts of occupancy information collected from connected vehicles (CVs) on urban signal controls and potential benefits to person-related performance that those information can bring. The contributions of this study include: 1) development of a three-layered DP person-based signal control mechanism (PerSiCon-Junction) in a fully CV environment at an isolated junction with a signal phase transition exploration mechanism and car-following updating theories; 2) development of a person-based control mechanism (PerSiCon-Bus) with completely flexible signal plans to apply the PerSiCon-Junction to more complex vehicle mixtures of cars and buses in a generalized 8-phases options junction; 3) proposal of a coordinated paradigm PerSiCon-Network to better understand how PerSiCon-Bus with flexible phase combinations and stage sequences should be implemented in multiple junctions; 4) realistic case and scenarios studies that assess the performance of the proposed method against benchmarking models involving vehicle-based controls using CV data; and 5) proposal of a EUVO algorithm to estimate status of unequipped vehicles with occupancy so as to improve the behaviour of PerSiCon-Network under imperfect CV penetration rate environments.

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Submitted date: November 2022
Published date: 2023

Identifiers

Local EPrints ID: 474088
URI: http://eprints.soton.ac.uk/id/eprint/474088
PURE UUID: e5497e4a-471b-4400-94f1-ed1e65b818c6
ORCID for Benedict Waterson: ORCID iD orcid.org/0000-0001-9817-7119

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Date deposited: 13 Feb 2023 17:47
Last modified: 11 Apr 2024 04:01

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Contributors

Author: Zongyuan Wu
Thesis advisor: Benedict Waterson ORCID iD

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