PRECOM: A Parallel Recommendation Engine for Control, Operations, and Management on Congested Urban Traffic Networks

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Fältnamn	Indikatorer	Metadata
000		04079naa a2200637 4500
001		oai:DiVA.org:kth-308831
003		SwePub
008		220215s2021 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
024	7	a https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3088312 URI
024	7	a https://doi.org/10.1109/TITS.2021.30688742 DOI
040		a (SwePub)kth
041		a engb eng
042		9 SwePub
072	7	a ref2 swepub-contenttype
072	7	a art2 swepub-publicationtype
100	1	a Jin, Junchenu KTH,Byggvetenskap,Enjoyor Company Ltd., Hangzhou 310030, China; the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.4 aut0 (Swepub:kth)u1mcg76o
245	1 0	a PRECOM :b A Parallel Recommendation Engine for Control, Operations, and Management on Congested Urban Traffic Networks
264	1	b Institute of Electrical and Electronics Engineers (IEEE),c 2021
338		a print2 rdacarrier
500		a QC 20221031
520		a This paper proposes a parallel recommendation engine, PRECOM, for traffic control operations to mitigate congestion of road traffic in the metropolitan area. The recommendation engine can provide, in real-time, effective and optimal control plans to traffic engineers, who are responsible for manually calibrating traffic signal plans especially when a road network suffers from heavy congestion due to disruptive events. With the idea of incorporating expert knowledge in the operation loop, the PRECOM system is designed to include three conceptual components: an artificial system model, a computational experiment module, and a parallel execution module. Meanwhile, three essential algorithmic steps are implemented in the recommendation engine: a candidate generator based on a graph model, a spatiotemporal ranker, and a context-aware re-ranker. The PRECOM system has been deployed in the city of Hangzhou, China, through both offline and online evaluation. The experimental results are promising, and prove that the recommendation system can provide effective support to the current human-in-the-loop control scheme in the practice of traffic control, operations, and management.
650	7	a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Reglerteknik0 (SwePub)202022 hsv//swe
650	7	a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Control Engineering0 (SwePub)202022 hsv//eng
650	7	a TEKNIK OCH TEKNOLOGIERx Samhällsbyggnadsteknikx Transportteknik och logistik0 (SwePub)201052 hsv//swe
650	7	a ENGINEERING AND TECHNOLOGYx Civil Engineeringx Transport Systems and Logistics0 (SwePub)201052 hsv//eng
653		a human-in-the-loop system.
653		a parallel traffic management
653		a Spatial-temporal recommender system
653		a urban traffic control
653		a Engines
653		a Highway administration
653		a Knowledge based systems
653		a Metropolitan area networks
653		a Roads and streets
653		a Traffic congestion
653		a Traffic signals
653		a Uncertainty analysis
653		a Artificial systems
653		a Computational experiment
653		a Control operations
653		a Human-in-the-loop control
653		a Metropolitan area
653		a On-line evaluation
653		a Parallel executions
653		a Urban traffic networks
653		a Recommender systems
700	1	a Rong, D.4 aut
700	1	a Pang, Y.4 aut
700	1	a Zhu, F.4 aut
700	1	a Guo, H.4 aut
700	1	a Ma, Xiaoliang,c Docentu KTH,Transportplanering4 aut0 (Swepub:kth)u1i7xzbr
700	1	a Wang, F.4 aut
710	2	a KTHb Byggvetenskap4 org
773	0	t IEEE transactions on intelligent transportation systems (Print)d : Institute of Electrical and Electronics Engineers (IEEE)g , s. 1-11q <1-11x 1524-9050x 1558-0016
856	4 8	u https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-308831
856	4 8	u https://doi.org/10.1109/TITS.2021.3068874

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Av författaren/redakt...: Jin, Junchen; Rong, D.; Pang, Y.; Zhu, F.; Guo, H.; Ma, Xiaoliang, D ...; visa fler...; Wang, F.; visa färre...

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