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Sökning: L773:0197 6729 OR L773:2042 3195 > Modelling public tr...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00003620naa a2200493 4500
001oai:DiVA.org:kth-195286
003SwePub
008161102s2016 | |||||||||||000 ||eng|
024a https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-1952862 URI
024a https://doi.org/10.1002/atr.13982 DOI
040 a (SwePub)kth
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
100a Cats, Odedu KTH,Transportplanering, ekonomi och teknik,Delft University of Technology, Netherlands4 aut0 (Swepub:kth)u1vn3rdr
2451 0a Modelling public transport on-board congestion :b comparing schedule-based and agent-based assignment approaches and their implications
264 c 2016-10-06
264 1b Wiley-Blackwell,c 2016
338 a print2 rdacarrier
500 a QC 20161111
520 a Transit systems are subject to congestion that influences system performance and level of service. The evaluation of measures to relieve congestion requires models that can capture their network effects and passengers' adaptation. In particular, on-board congestion leads to an increase of crowding discomfort and denied boarding and a decrease in service reliability. This study performs a systematic comparison of alternative approaches to modelling on-board congestion in transit networks. In particular, the congestion-related functionalities of a schedule-based model and an agent-based transit assignment model are investigated, by comparing VISUM and BusMezzo, respectively. The theoretical background, modelling principles and implementation details of the alternative models are examined and demonstrated by testing various operational scenarios for an example network. The results suggest that differences in modelling passenger arrival process, choice-set generation and route choice model yield systematically different passenger loads. The schedule-based model is insensitive to a uniform increase in demand or decrease in capacity when caused by either vehicle capacity or service frequency reduction. In contrast, nominal travel times increase in the agent-based model as demand increases or capacity decreases. The marginal increase in travel time increases as the network becomes more saturated. Whilst none of the existing models capture the full range of congestion effects and related behavioural responses, existing models can support different planning decisions.
650 7a TEKNIK OCH TEKNOLOGIERx Samhällsbyggnadsteknikx Transportteknik och logistik0 (SwePub)201052 hsv//swe
650 7a ENGINEERING AND TECHNOLOGYx Civil Engineeringx Transport Systems and Logistics0 (SwePub)201052 hsv//eng
653 a capacity
653 a congestion
653 a model comparison
653 a network assignment
653 a public transport
653 a simulation model
653 a transit networks
653 a Autonomous agents
653 a Computational methods
653 a Mass transportation
653 a Traffic control
653 a Transportation
653 a Travel time
653 a Traffic congestion
700a Hartl, M.4 aut
710a KTHb Transportplanering, ekonomi och teknik4 org
773t Journal of Advanced Transportationd : Wiley-Blackwellg 50:6, s. 1209-1224q 50:6<1209-1224x 0197-6729x 2042-3195
856u https://repository.tudelft.nl/islandora/object/uuid%3Af8d71242-d02e-4d83-b264-3cd7bf88b0a9/datastream/OBJ/download
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-195286
8564 8u https://doi.org/10.1002/atr.1398

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Cats, Oded
Hartl, M.
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