Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity

Emergency events can induce serious traffic congestions in a local area which may propagate to the upstream roads, and even the whole network. Until now, the methodology forecasting spatiotemporal boundary propagation of emergency-event-based traffic congestions, with both explicitness and road netw...

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Autores principales:	Xingliang Liu, Jian Wang, Tangzhi Liu, Jin Xu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	spatiotemporal boundary emergency event expressway network HNAC traffic incident cases Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/24b7ea5704af4178ae80aaf9ac29e507
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id	oai:doaj.org-article:24b7ea5704af4178ae80aaf9ac29e507
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spelling	oai:doaj.org-article:24b7ea5704af4178ae80aaf9ac29e5072021-11-11T19:47:32ZForecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity10.3390/su1321121952071-1050https://doaj.org/article/24b7ea5704af4178ae80aaf9ac29e5072021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/21/12195https://doaj.org/toc/2071-1050Emergency events can induce serious traffic congestions in a local area which may propagate to the upstream roads, and even the whole network. Until now, the methodology forecasting spatiotemporal boundary propagation of emergency-event-based traffic congestions, with both explicitness and road network availability, has not been found. This study develops a new method for predicting spatiotemporal boundary of the congestion caused by emergency events, which is more applicable and practical than cell transmission model (CTM)-derived methods. This method divides the expressway network into different sections based on their functions and the shockwave direction caused by the emergency events. It characterizes the velocity of the moving congestion boundary based on kinetic wave theory and volume–density relationship. After determining whether the congestion will spread into the network level through an interchange using a new concept, highway node acceptance capacity (HNAC), we can predict the spatiotemporal boundary and corresponding traffic condition within the boundary. The proposed method is tested under four traffic incident cases with corresponding traffic data collected through field observations. We also compare its prediction performances with other methods used in the literature.Xingliang LiuJian WangTangzhi LiuJin XuMDPI AGarticlespatiotemporal boundaryemergency eventexpressway networkHNACtraffic incident casesEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12195, p 12195 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	spatiotemporal boundary emergency event expressway network HNAC traffic incident cases Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	spatiotemporal boundary emergency event expressway network HNAC traffic incident cases Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Xingliang Liu Jian Wang Tangzhi Liu Jin Xu Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity
description	Emergency events can induce serious traffic congestions in a local area which may propagate to the upstream roads, and even the whole network. Until now, the methodology forecasting spatiotemporal boundary propagation of emergency-event-based traffic congestions, with both explicitness and road network availability, has not been found. This study develops a new method for predicting spatiotemporal boundary of the congestion caused by emergency events, which is more applicable and practical than cell transmission model (CTM)-derived methods. This method divides the expressway network into different sections based on their functions and the shockwave direction caused by the emergency events. It characterizes the velocity of the moving congestion boundary based on kinetic wave theory and volume–density relationship. After determining whether the congestion will spread into the network level through an interchange using a new concept, highway node acceptance capacity (HNAC), we can predict the spatiotemporal boundary and corresponding traffic condition within the boundary. The proposed method is tested under four traffic incident cases with corresponding traffic data collected through field observations. We also compare its prediction performances with other methods used in the literature.
format	article
author	Xingliang Liu Jian Wang Tangzhi Liu Jin Xu
author_facet	Xingliang Liu Jian Wang Tangzhi Liu Jin Xu
author_sort	Xingliang Liu
title	Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity
title_short	Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity
title_full	Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity
title_fullStr	Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity
title_full_unstemmed	Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity
title_sort	forecasting spatiotemporal boundary of emergency-event-based traffic congestion in expressway network considering highway node acceptance capacity
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/24b7ea5704af4178ae80aaf9ac29e507
work_keys_str_mv	AT xingliangliu forecastingspatiotemporalboundaryofemergencyeventbasedtrafficcongestioninexpresswaynetworkconsideringhighwaynodeacceptancecapacity AT jianwang forecastingspatiotemporalboundaryofemergencyeventbasedtrafficcongestioninexpresswaynetworkconsideringhighwaynodeacceptancecapacity AT tangzhiliu forecastingspatiotemporalboundaryofemergencyeventbasedtrafficcongestioninexpresswaynetworkconsideringhighwaynodeacceptancecapacity AT jinxu forecastingspatiotemporalboundaryofemergencyeventbasedtrafficcongestioninexpresswaynetworkconsideringhighwaynodeacceptancecapacity
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Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity

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