A Quantitative Method to Delineate the Influence Area of Work Zone Considering Route Choice Inertia and Elastic Demand
The work zone on the urban road network will affect the surrounding road traffic. To represent the influence area of the work zone, the concept of a subnetwork is proposed in this paper. Delineating a suitable subnetwork quantitatively is a challenging problem. To address this issue, the node synthe...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/2507107 |
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| _version_ | 1832553651628933120 |
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| author | Guanfeng Wang Hongfei Jia Jingjing Tian Yu Lin Ruiyi Wu Zhendong Liu Heyao Gao |
| author_facet | Guanfeng Wang Hongfei Jia Jingjing Tian Yu Lin Ruiyi Wu Zhendong Liu Heyao Gao |
| author_sort | Guanfeng Wang |
| collection | DOAJ |
| description | The work zone on the urban road network will affect the surrounding road traffic. To represent the influence area of the work zone, the concept of a subnetwork is proposed in this paper. Delineating a suitable subnetwork quantitatively is a challenging problem. To address this issue, the node synthesized indexes (NSI) are deployed as a variability measure that captures both the change of link flow and origin-destination (OD) demand. The inertia-based stochastic user equilibrium with the elastic demand (ISUEED) model is proposed to accurately provide the data of link flow and OD demand for the network with the work zone. Correspondingly, the data of the network without a work zone can be obtained by the stochastic user equilibrium (SUE) model. According to the value of NSI, the initial range of the subnetwork is determined. Finally, the connectivity and compactness can be guaranteed by the modified L-shell algorithm. To demonstrate the performance of the method, two case studies and sensitivity analyses are conducted based on the Braess network and the local road network in Changchun, China. The proposed method is beneficial to reduce the complexity of the traffic model by substituting the entire network with a subnetwork. |
| format | Article |
| id | doaj-art-fa2a898a7c1a4fd5aac7ba30822ff4e5 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-fa2a898a7c1a4fd5aac7ba30822ff4e52025-02-03T05:53:40ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/2507107A Quantitative Method to Delineate the Influence Area of Work Zone Considering Route Choice Inertia and Elastic DemandGuanfeng Wang0Hongfei Jia1Jingjing Tian2Yu Lin3Ruiyi Wu4Zhendong Liu5Heyao Gao6College of TransportationCollege of TransportationCollege of TransportationFaculty of Maritime and TransportationCollege of TransportationCollege of TransportationCollege of TransportationThe work zone on the urban road network will affect the surrounding road traffic. To represent the influence area of the work zone, the concept of a subnetwork is proposed in this paper. Delineating a suitable subnetwork quantitatively is a challenging problem. To address this issue, the node synthesized indexes (NSI) are deployed as a variability measure that captures both the change of link flow and origin-destination (OD) demand. The inertia-based stochastic user equilibrium with the elastic demand (ISUEED) model is proposed to accurately provide the data of link flow and OD demand for the network with the work zone. Correspondingly, the data of the network without a work zone can be obtained by the stochastic user equilibrium (SUE) model. According to the value of NSI, the initial range of the subnetwork is determined. Finally, the connectivity and compactness can be guaranteed by the modified L-shell algorithm. To demonstrate the performance of the method, two case studies and sensitivity analyses are conducted based on the Braess network and the local road network in Changchun, China. The proposed method is beneficial to reduce the complexity of the traffic model by substituting the entire network with a subnetwork.http://dx.doi.org/10.1155/2022/2507107 |
| spellingShingle | Guanfeng Wang Hongfei Jia Jingjing Tian Yu Lin Ruiyi Wu Zhendong Liu Heyao Gao A Quantitative Method to Delineate the Influence Area of Work Zone Considering Route Choice Inertia and Elastic Demand Journal of Advanced Transportation |
| title | A Quantitative Method to Delineate the Influence Area of Work Zone Considering Route Choice Inertia and Elastic Demand |
| title_full | A Quantitative Method to Delineate the Influence Area of Work Zone Considering Route Choice Inertia and Elastic Demand |
| title_fullStr | A Quantitative Method to Delineate the Influence Area of Work Zone Considering Route Choice Inertia and Elastic Demand |
| title_full_unstemmed | A Quantitative Method to Delineate the Influence Area of Work Zone Considering Route Choice Inertia and Elastic Demand |
| title_short | A Quantitative Method to Delineate the Influence Area of Work Zone Considering Route Choice Inertia and Elastic Demand |
| title_sort | quantitative method to delineate the influence area of work zone considering route choice inertia and elastic demand |
| url | http://dx.doi.org/10.1155/2022/2507107 |
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