Route Guidance Model with Limited Overlap on Freeway Network under Traffic Incidents
With the increasing density of the freeway network, frequent traffic incidents on road segments have a significant impact on the operational efficiency of the road network. Therefore, it has become urgent and important to study traffic route guidance strategy on the road network level. The previous...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2024/4250807 |
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| _version_ | 1832546174757765120 |
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| author | Xuan Zhang Jinjun Tang Chengcheng Wang Chao Wang |
| author_facet | Xuan Zhang Jinjun Tang Chengcheng Wang Chao Wang |
| author_sort | Xuan Zhang |
| collection | DOAJ |
| description | With the increasing density of the freeway network, frequent traffic incidents on road segments have a significant impact on the operational efficiency of the road network. Therefore, it has become urgent and important to study traffic route guidance strategy on the road network level. The previous traffic route guidance method primarily focused on the congestion on the road segments where incidents occurred, with insufficient attention given to the impact of congestion on the road network level. In this study, a route guidance model with limited overlap is proposed to improve freeway network reliability under traffic incidents. Specifically, in order to explore alternative paths, we conducted a study on the problem of finding k-short paths with limited overlap. The objective is to identify a set of k-paths that are both sufficiently dissimilar and as short as possible. Then, we promptly update the route guidance information using a stochastic dynamic traffic assignment model that aligns with travelers’ path choice psychology. Moreover, we use the reliability of the road network to evaluate the network performance. To illustrate the model, the Jinan freeway network is selected as an experimental study. The effectiveness of this method was validated through SUMO simulations, comparing it with alternative route guidance methods, including Yen’s algorithm, A∗ algorithm, and ant colony algorithm. These results show that the proposed method has proven effective in mitigating traffic congestion arising from incidents and performs well in regard to the reliability of the road network under the impact of incidents. |
| format | Article |
| id | doaj-art-06f565d96c7643f383beb62a6e0afd3b |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-06f565d96c7643f383beb62a6e0afd3b2025-02-03T07:23:37ZengWileyJournal of Advanced Transportation2042-31952024-01-01202410.1155/2024/4250807Route Guidance Model with Limited Overlap on Freeway Network under Traffic IncidentsXuan Zhang0Jinjun Tang1Chengcheng Wang2Chao Wang3School of Traffic and Transportation EngineeringSchool of Traffic and Transportation EngineeringShandong Provincial Communications Planning and Design Institute Group Co., LtdShandong Provincial Communications Planning and Design Institute Group Co., LtdWith the increasing density of the freeway network, frequent traffic incidents on road segments have a significant impact on the operational efficiency of the road network. Therefore, it has become urgent and important to study traffic route guidance strategy on the road network level. The previous traffic route guidance method primarily focused on the congestion on the road segments where incidents occurred, with insufficient attention given to the impact of congestion on the road network level. In this study, a route guidance model with limited overlap is proposed to improve freeway network reliability under traffic incidents. Specifically, in order to explore alternative paths, we conducted a study on the problem of finding k-short paths with limited overlap. The objective is to identify a set of k-paths that are both sufficiently dissimilar and as short as possible. Then, we promptly update the route guidance information using a stochastic dynamic traffic assignment model that aligns with travelers’ path choice psychology. Moreover, we use the reliability of the road network to evaluate the network performance. To illustrate the model, the Jinan freeway network is selected as an experimental study. The effectiveness of this method was validated through SUMO simulations, comparing it with alternative route guidance methods, including Yen’s algorithm, A∗ algorithm, and ant colony algorithm. These results show that the proposed method has proven effective in mitigating traffic congestion arising from incidents and performs well in regard to the reliability of the road network under the impact of incidents.http://dx.doi.org/10.1155/2024/4250807 |
| spellingShingle | Xuan Zhang Jinjun Tang Chengcheng Wang Chao Wang Route Guidance Model with Limited Overlap on Freeway Network under Traffic Incidents Journal of Advanced Transportation |
| title | Route Guidance Model with Limited Overlap on Freeway Network under Traffic Incidents |
| title_full | Route Guidance Model with Limited Overlap on Freeway Network under Traffic Incidents |
| title_fullStr | Route Guidance Model with Limited Overlap on Freeway Network under Traffic Incidents |
| title_full_unstemmed | Route Guidance Model with Limited Overlap on Freeway Network under Traffic Incidents |
| title_short | Route Guidance Model with Limited Overlap on Freeway Network under Traffic Incidents |
| title_sort | route guidance model with limited overlap on freeway network under traffic incidents |
| url | http://dx.doi.org/10.1155/2024/4250807 |
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