Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/185626
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dc.contributor.authorZhiyi Lien_US
dc.contributor.authorMohammad Shahidehpouren_US
dc.contributor.authorShay Bahramiraden_US
dc.contributor.authorAmin Khodaeien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:36:56Z-
dc.date.available2020-04-06T07:36:56Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TSG.2016.2526032en_US
dc.identifier.urihttp://localhost/handle/Hannan/185626-
dc.description.abstractTraffic signals play a critical role in smart cities for mitigating traffic congestions and reducing the emission in metropolitan areas. This paper proposes a bi-level optimization framework to settle the optimal traffic signal setting problem. The upper-level problem determines the traffic signal settings to minimize the drivers' average travel time, while the lower-level problem aims for achieving the network equilibrium using the settings calculated at the upper level. Genetic algorithm is employed with the integration of microscopic-traffic-simulation-based dynamic traffic assignment (DTA) to decouple the complex bi-level problem into tractable single-level problems, which are solved sequentially. Case studies on a synthetic traffic network and a real-world traffic subnetwork are conducted to examine the effectiveness of the proposed model and relevant solution methods. Additional strategies are provided for the extension of the proposed model and the acceleration of solution process in large-area traffic network applications.en_US
dc.format.extent2382,en_US
dc.format.extent2393en_US
dc.publisherIEEEen_US
dc.relation.haspart7438878.pdfen_US
dc.titleOptimizing Traffic Signal Settings in Smart Citiesen_US
dc.typeArticleen_US
dc.journal.volume8en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7438878.pdf406.65 kBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZhiyi Lien_US
dc.contributor.authorMohammad Shahidehpouren_US
dc.contributor.authorShay Bahramiraden_US
dc.contributor.authorAmin Khodaeien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:36:56Z-
dc.date.available2020-04-06T07:36:56Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TSG.2016.2526032en_US
dc.identifier.urihttp://localhost/handle/Hannan/185626-
dc.description.abstractTraffic signals play a critical role in smart cities for mitigating traffic congestions and reducing the emission in metropolitan areas. This paper proposes a bi-level optimization framework to settle the optimal traffic signal setting problem. The upper-level problem determines the traffic signal settings to minimize the drivers' average travel time, while the lower-level problem aims for achieving the network equilibrium using the settings calculated at the upper level. Genetic algorithm is employed with the integration of microscopic-traffic-simulation-based dynamic traffic assignment (DTA) to decouple the complex bi-level problem into tractable single-level problems, which are solved sequentially. Case studies on a synthetic traffic network and a real-world traffic subnetwork are conducted to examine the effectiveness of the proposed model and relevant solution methods. Additional strategies are provided for the extension of the proposed model and the acceleration of solution process in large-area traffic network applications.en_US
dc.format.extent2382,en_US
dc.format.extent2393en_US
dc.publisherIEEEen_US
dc.relation.haspart7438878.pdfen_US
dc.titleOptimizing Traffic Signal Settings in Smart Citiesen_US
dc.typeArticleen_US
dc.journal.volume8en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7438878.pdf406.65 kBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZhiyi Lien_US
dc.contributor.authorMohammad Shahidehpouren_US
dc.contributor.authorShay Bahramiraden_US
dc.contributor.authorAmin Khodaeien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:36:56Z-
dc.date.available2020-04-06T07:36:56Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TSG.2016.2526032en_US
dc.identifier.urihttp://localhost/handle/Hannan/185626-
dc.description.abstractTraffic signals play a critical role in smart cities for mitigating traffic congestions and reducing the emission in metropolitan areas. This paper proposes a bi-level optimization framework to settle the optimal traffic signal setting problem. The upper-level problem determines the traffic signal settings to minimize the drivers' average travel time, while the lower-level problem aims for achieving the network equilibrium using the settings calculated at the upper level. Genetic algorithm is employed with the integration of microscopic-traffic-simulation-based dynamic traffic assignment (DTA) to decouple the complex bi-level problem into tractable single-level problems, which are solved sequentially. Case studies on a synthetic traffic network and a real-world traffic subnetwork are conducted to examine the effectiveness of the proposed model and relevant solution methods. Additional strategies are provided for the extension of the proposed model and the acceleration of solution process in large-area traffic network applications.en_US
dc.format.extent2382,en_US
dc.format.extent2393en_US
dc.publisherIEEEen_US
dc.relation.haspart7438878.pdfen_US
dc.titleOptimizing Traffic Signal Settings in Smart Citiesen_US
dc.typeArticleen_US
dc.journal.volume8en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7438878.pdf406.65 kBAdobe PDF