서브메뉴
검색
Traffic Signal Optimization With Connected Vehicle Trajectories- [electronic resource]
![Traffic Signal Optimization With Connected Vehicle Trajectories - [electronic resource]](/Users/Baul/Images/book.png)
Traffic Signal Optimization With Connected Vehicle Trajectories- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214101945
- ISBN
- 9798380371117
- DDC
- 624
- 저자명
- Wang, Xingmin.
- 서명/저자
- Traffic Signal Optimization With Connected Vehicle Trajectories - [electronic resource]
- 발행사항
- [S.l.]: : University of Michigan., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(155 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
- 주기사항
- Advisor: Liu, Henry.
- 학위논문주기
- Thesis (Ph.D.)--University of Michigan, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 사용제한주기
- This item must not be added to any third party search indexes.
- 초록/해제
- 요약Traffic signal re-timing is one of the most cost-effective methods for reducing congestion and energy consumption in urban areas based on the existing road infrastructure. However, high installation and maintenance costs of vehicle detectors have prevented the widespread implementation of adaptive traffic signal control system (ATSC). In the past few years, vehicle trajectory data has become increasingly available and offers many advantages over detectors and other infrastructure-based sensors for traffic monitoring. However, one major challenge of using vehicle trajectory data for traffic signal re-timing is the data sparsity and incompleteness caused by the limited penetration rate.This dissertation aims at providing systematic methods for traffic signal optimization with vehicle trajectory data at the current market penetration rate (≤ 10%). The main contribution is the newly proposed stochastic traffic flow model under Newellian coordinates, which is established based on Newell's simplified car-following model. We show that a point-queue model under the Newellian coordinates can sufficiently capture the whole spatial-temporal traffic state through the PTS diagram. This simplification is made feasible by ignoring the stochastic driving behavior since most of the system uncertainty comes from the stochastic traffic demand as well as sparse observation at a low penetration rate. The main advantage of the proposed model is that it is a stochastic model with much lower dimensions and can be directly calibrated by taking the vehicle trajectory data as the input. It enables us to apply different statistical estimation algorithms to estimate both stationary traffic parameters (i.e., penetration rate, average arrival rate, etc.) and real-time traffic state (queue length). Based on the estimated traffic state and parameters, we also develop different optimization programs for the re-timing of fixed-time traffic signals and a rule-based queue clearance control (QCC) for real-time traffic signals.With the proposed methods, we develop an integrated traffic signal re-timing system called Optimizing traffic Signals as a Service (OSaaS). In April 2022, a citywide field test of OSaaS was conducted in Birmingham, Michigan, with 34 signalized intersections. 2 corridors and 2 isolated intersections were implemented with new fixed-time signal timing plans, resulting in decreases in both the delay and number of stops by up to 20% and 30%, respectively. OSaaS is a closed-loop iterative system including performance evaluation, traffic state estimation, traffic signal diagnosis, and optimization. By not requiring installation or maintenance of vehicle detectors, OSaaS provides a more scalable, sustainable, resilient, responsive, and efficient solution to traffic signal re-timing based on vehicle trajectory, which could be applied to every traffic signal in the world.
- 일반주제명
- Civil engineering.
- 일반주제명
- Transportation.
- 일반주제명
- Urban planning.
- 기타저자
- University of Michigan Civil Engineering
- 기본자료저록
- Dissertations Abstracts International. 85-03B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008240612s2023 us |||||||||||||||c||eng d■001000016935538
■00520240214101945
■006m o d
■007cr#unu||||||||
■020 ▼a9798380371117
■035 ▼a(MiAaPQ)AAI30747498
■035 ▼a(MiAaPQ)umichrackham005246
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a624
■1001 ▼aWang, Xingmin.
■24510▼aTraffic Signal Optimization With Connected Vehicle Trajectories▼h[electronic resource]
■260 ▼a[S.l.]:▼bUniversity of Michigan. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(155 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-03, Section: B.
■500 ▼aAdvisor: Liu, Henry.
■5021 ▼aThesis (Ph.D.)--University of Michigan, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■506 ▼aThis item must not be added to any third party search indexes.
■520 ▼aTraffic signal re-timing is one of the most cost-effective methods for reducing congestion and energy consumption in urban areas based on the existing road infrastructure. However, high installation and maintenance costs of vehicle detectors have prevented the widespread implementation of adaptive traffic signal control system (ATSC). In the past few years, vehicle trajectory data has become increasingly available and offers many advantages over detectors and other infrastructure-based sensors for traffic monitoring. However, one major challenge of using vehicle trajectory data for traffic signal re-timing is the data sparsity and incompleteness caused by the limited penetration rate.This dissertation aims at providing systematic methods for traffic signal optimization with vehicle trajectory data at the current market penetration rate (≤ 10%). The main contribution is the newly proposed stochastic traffic flow model under Newellian coordinates, which is established based on Newell's simplified car-following model. We show that a point-queue model under the Newellian coordinates can sufficiently capture the whole spatial-temporal traffic state through the PTS diagram. This simplification is made feasible by ignoring the stochastic driving behavior since most of the system uncertainty comes from the stochastic traffic demand as well as sparse observation at a low penetration rate. The main advantage of the proposed model is that it is a stochastic model with much lower dimensions and can be directly calibrated by taking the vehicle trajectory data as the input. It enables us to apply different statistical estimation algorithms to estimate both stationary traffic parameters (i.e., penetration rate, average arrival rate, etc.) and real-time traffic state (queue length). Based on the estimated traffic state and parameters, we also develop different optimization programs for the re-timing of fixed-time traffic signals and a rule-based queue clearance control (QCC) for real-time traffic signals.With the proposed methods, we develop an integrated traffic signal re-timing system called Optimizing traffic Signals as a Service (OSaaS). In April 2022, a citywide field test of OSaaS was conducted in Birmingham, Michigan, with 34 signalized intersections. 2 corridors and 2 isolated intersections were implemented with new fixed-time signal timing plans, resulting in decreases in both the delay and number of stops by up to 20% and 30%, respectively. OSaaS is a closed-loop iterative system including performance evaluation, traffic state estimation, traffic signal diagnosis, and optimization. By not requiring installation or maintenance of vehicle detectors, OSaaS provides a more scalable, sustainable, resilient, responsive, and efficient solution to traffic signal re-timing based on vehicle trajectory, which could be applied to every traffic signal in the world.
■590 ▼aSchool code: 0127.
■650 4▼aCivil engineering.
■650 4▼aTransportation.
■650 4▼aUrban planning.
■653 ▼aTraffic signal control
■653 ▼aTraffic flow model
■653 ▼aTraffic state estimation
■653 ▼aBayesian estimation
■653 ▼aEnergy consumption
■690 ▼a0543
■690 ▼a0709
■690 ▼a0999
■71020▼aUniversity of Michigan▼bCivil Engineering.
■7730 ▼tDissertations Abstracts International▼g85-03B.
■773 ▼tDissertation Abstract International
■790 ▼a0127
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16935538▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
