Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network
Traffic congestion has been a hot topic of research in the field of intelligent transportation, which can be alleviated by efficient route navigation. Most of the existing route planning methods are non-negotiated algorithms, which do not take into account the route conflicts and collaborative relat...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hindawi-Wiley
2023-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/3770800 |
| _version_ | 1797372214347038720 |
|---|---|
| author | Liping Yan Yue Tang Chan Peng Yu Cai Wenbo Zhang Jing Wang |
| author_facet | Liping Yan Yue Tang Chan Peng Yu Cai Wenbo Zhang Jing Wang |
| author_sort | Liping Yan |
| collection | DOAJ |
| description | Traffic congestion has been a hot topic of research in the field of intelligent transportation, which can be alleviated by efficient route navigation. Most of the existing route planning methods are non-negotiated algorithms, which do not take into account the route conflicts and collaborative relationships between multiple vehicles. Also, most negotiated algorithms have not been comprehensively considered dynamic route collaboration between vehicles, large-scale efficient computation, environmental pollution, etc. Therefore, an ecological multivehicle real-time route selection model (EMR2SM) for urban road networks is firstly proposed in this paper, which combines real-time traffic conditions of the road network with travel time, distance, and exhaust emissions as optimization indicators. In order to solve the large-scale computation problem of traditional negotiated algorithms, an adaptive multiswarm bee colony (AMSBC) algorithm is designed, which efficiently solves the multivehicle dynamic route selection problem. AMSBC searches the optimal route for each vehicle in parallel through multiple population division and self-adaption mechanism, to make multivehicle route selection reach Nash equilibrium. Compared with three non-negotiated optimization algorithms based on swarm technology, EMR2SM is verified by experiments that it improves the efficiency and accuracy of the optimal route selection for multiple vehicles and reduces vehicle emissions, which can effectively reduce traffic congestion and environmental pollution. |
| first_indexed | 2024-03-08T18:31:36Z |
| format | Article |
| id | doaj.art-430dc7c47513480f96c484b07140e864 |
| institution | Directory Open Access Journal |
| issn | 2042-3195 |
| language | English |
| last_indexed | 2024-03-08T18:31:36Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi-Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj.art-430dc7c47513480f96c484b07140e8642023-12-30T00:00:03ZengHindawi-WileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/3770800Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road NetworkLiping Yan0Yue Tang1Chan Peng2Yu Cai3Wenbo Zhang4Jing Wang5Software SchoolSoftware SchoolSoftware SchoolSoftware SchoolSoftware SchoolSoftware SchoolTraffic congestion has been a hot topic of research in the field of intelligent transportation, which can be alleviated by efficient route navigation. Most of the existing route planning methods are non-negotiated algorithms, which do not take into account the route conflicts and collaborative relationships between multiple vehicles. Also, most negotiated algorithms have not been comprehensively considered dynamic route collaboration between vehicles, large-scale efficient computation, environmental pollution, etc. Therefore, an ecological multivehicle real-time route selection model (EMR2SM) for urban road networks is firstly proposed in this paper, which combines real-time traffic conditions of the road network with travel time, distance, and exhaust emissions as optimization indicators. In order to solve the large-scale computation problem of traditional negotiated algorithms, an adaptive multiswarm bee colony (AMSBC) algorithm is designed, which efficiently solves the multivehicle dynamic route selection problem. AMSBC searches the optimal route for each vehicle in parallel through multiple population division and self-adaption mechanism, to make multivehicle route selection reach Nash equilibrium. Compared with three non-negotiated optimization algorithms based on swarm technology, EMR2SM is verified by experiments that it improves the efficiency and accuracy of the optimal route selection for multiple vehicles and reduces vehicle emissions, which can effectively reduce traffic congestion and environmental pollution.http://dx.doi.org/10.1155/2023/3770800 |
| spellingShingle | Liping Yan Yue Tang Chan Peng Yu Cai Wenbo Zhang Jing Wang Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network Journal of Advanced Transportation |
| title | Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network |
| title_full | Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network |
| title_fullStr | Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network |
| title_full_unstemmed | Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network |
| title_short | Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network |
| title_sort | ecological and real time route selection method for multiple vehicles in urban road network |
| url | http://dx.doi.org/10.1155/2023/3770800 |
| work_keys_str_mv | AT lipingyan ecologicalandrealtimerouteselectionmethodformultiplevehiclesinurbanroadnetwork AT yuetang ecologicalandrealtimerouteselectionmethodformultiplevehiclesinurbanroadnetwork AT chanpeng ecologicalandrealtimerouteselectionmethodformultiplevehiclesinurbanroadnetwork AT yucai ecologicalandrealtimerouteselectionmethodformultiplevehiclesinurbanroadnetwork AT wenbozhang ecologicalandrealtimerouteselectionmethodformultiplevehiclesinurbanroadnetwork AT jingwang ecologicalandrealtimerouteselectionmethodformultiplevehiclesinurbanroadnetwork |