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Real-time merging traffic control for throughput maximization at motorway work zones
Technical University of Crete, Greece .
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2014 (English)In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 44, p. 242-252Article in journal (Refereed) Published
Abstract [en]

Work zones on motorways necessitate the drop of one or more lanes which may lead to significant reduction of traffic flow capacity and efficiency, traffic flow disruptions, congestion creation, and increased accident risk. Real-time traffic control by use of green-red traffic signals at the motorway mainstream is proposed in order to achieve safer merging of vehicles entering the work zone and, at the same time, maximize throughput and reduce travel delays. A significant issue that had been neglected in previous research is the investigation of the impact of distance between the merge area and the traffic lights so as to achieve, in combination with the employed real-time traffic control strategy, the most efficient merging of vehicles. The control strategy applied for real-time signal operation is based on an ALINEA-like proportional-integral (PI-type) feedback regulator. In order to achieve maximum performance of the control strategy, some calibration of the regulator's parameters may be necessary. The calibration is first conducted manually, via a typical trial-and-error procedure. In an additional investigation, the recently proposed learning/adaptive fine-tuning (AFT) algorithm is employed in order to automatically fine-tune the regulator parameters. Experiments conducted with a microscopic simulator for a hypothetical work zone infrastructure, demonstrate the potential high benefits of the control scheme.

Place, publisher, year, edition, pages
2014. Vol. 44, p. 242-252
Keywords [en]
Work zone management, Feedback control, Merging traffic control, Adaptive fine-tuning (AFT), Regulator fine-tuning
National Category
Other Civil Engineering
Identifiers
URN: urn:nbn:se:kth:diva-149215DOI: 10.1016/j.trc.2014.04.006ISI: 000339037100016Scopus ID: 2-s2.0-84900303467OAI: oai:DiVA.org:kth-149215DiVA, id: diva2:738722
Note

QC 20140819

Available from: 2014-08-19 Created: 2014-08-18 Last updated: 2018-01-29Bibliographically approved
In thesis
1. Demand Estimation and Bottleneck Management Using Heterogeneous Traffic Data
Open this publication in new window or tab >>Demand Estimation and Bottleneck Management Using Heterogeneous Traffic Data
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Congestion on urban and freeway networks has become a major problem, leading to increased travel times and reduced traffic safety. In order to suggest traffic management solutions to improve the transport system efficiency, it is important to capture the travel demand patterns, expressed as origin-destination (OD) matrices, and understand the mechanisms of traffic bottlenecks. The increasing availability of traffic data offers significant opportunities to effectively address these issues. The thesis uses heterogeneous traffic data to improve three important problems.

The first problem relates to the dynamic OD estimation problem, which entails significant challenges due to its complexity. The Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm has been commonly used to solve the problem, which can handle any available data that can improve the estimation accuracy. However, it encounters stability and convergence issues. The thesis proposes a general modification of SPSA, called cluster-wise SPSA (c-SPSA), that has more robust performance and finds better solutions. Its efficiency is demonstrated through simulation experiments for a network from Stockholm.

The second problem focuses on the development of methods for utilizing heterogeneous traffic data for the analysis and management of freeway work zone and tunnel bottlenecks. Simulation is used as the means to evaluate and optimize various mitigation strategies for each case.

The third problem analyzes multimodal impacts due to network disruptions for the case of tunnel bottlenecks, using a data-driven approach. Tunnel congestion is often dealt with temporary closures, which may cause significant disruptions. It is crucial to identify the potential multimodal impacts of such interventions so as to design efficient and proactive mitigation strategies. The thesis shows the benefits of combining multiple data sources to analyze the impacts of temporary tunnel closures for a freeway tunnel in Stockholm.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. 41
Series
TRITA-ABE-DLT ; 1802-001
National Category
Transport Systems and Logistics
Research subject
Transport Science
Identifiers
urn:nbn:se:kth:diva-221850 (URN)978-91-7729-663-8 (ISBN)
Public defence
2018-02-23, Kollegiesalen, Brinellvägen 8, Stockholm, 14:00 (English)
Opponent
Supervisors
Note

QC 20180129

Available from: 2018-01-29 Created: 2018-01-29 Last updated: 2018-01-29Bibliographically approved

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