Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion
The growth of urbanization, population, and economic activity has led to a substantial increase in freight transportation demand, exceeding the capacity of existing infrastructure and creating new challenges across various regions. This has resulted in significant traffic congestion, increased trave...
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MDPI AG
2024-11-01
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| Online Access: | https://www.mdpi.com/2076-3417/14/22/10134 |
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| author | Samar Younes Amr Oloufa |
| author_facet | Samar Younes Amr Oloufa |
| author_sort | Samar Younes |
| collection | DOAJ |
| description | The growth of urbanization, population, and economic activity has led to a substantial increase in freight transportation demand, exceeding the capacity of existing infrastructure and creating new challenges across various regions. This has resulted in significant traffic congestion, increased travel times, and higher operational costs for commercial vehicle fleets. Leveraging topological data, such as road networks and traffic patterns, can enable more efficient routing strategies to navigate around congested areas. This study presents a comprehensive approach to truck rerouting strategy by integrating spatial analysis, truck characteristics, traffic conditions, road geometry, and cost–benefit analysis to select alternative routes suitable for commercial vehicle fleets. Incorporating real-time traffic information and predictive analytics, commercial vehicle operators can optimize their routes, reduce fuel consumption, and improve overall delivery efficiency. Three case studies were presented to demonstrate the proposed diversion decision framework. Two scenarios were designed for each case study: a base scenario with no diversion and an optimized scenario with a diversion strategy. The travel times, fuel consumption, and economic impacts between the two scenarios were compared and quantified as a total annual saving of USD 52 million. This approach goes beyond selecting alternative routes and provides decision makers with measurable benefits that justify diversion strategies. |
| format | Article |
| id | doaj-art-dda48f9f969d4a4f91a5479d88509bd3 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-dda48f9f969d4a4f91a5479d88509bd32024-11-26T17:47:36ZengMDPI AGApplied Sciences2076-34172024-11-0114221013410.3390/app142210134Applying Topological Information for Routing Commercial Vehicles Around Traffic CongestionSamar Younes0Amr Oloufa1Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL 32816, USADepartment of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL 32816, USAThe growth of urbanization, population, and economic activity has led to a substantial increase in freight transportation demand, exceeding the capacity of existing infrastructure and creating new challenges across various regions. This has resulted in significant traffic congestion, increased travel times, and higher operational costs for commercial vehicle fleets. Leveraging topological data, such as road networks and traffic patterns, can enable more efficient routing strategies to navigate around congested areas. This study presents a comprehensive approach to truck rerouting strategy by integrating spatial analysis, truck characteristics, traffic conditions, road geometry, and cost–benefit analysis to select alternative routes suitable for commercial vehicle fleets. Incorporating real-time traffic information and predictive analytics, commercial vehicle operators can optimize their routes, reduce fuel consumption, and improve overall delivery efficiency. Three case studies were presented to demonstrate the proposed diversion decision framework. Two scenarios were designed for each case study: a base scenario with no diversion and an optimized scenario with a diversion strategy. The travel times, fuel consumption, and economic impacts between the two scenarios were compared and quantified as a total annual saving of USD 52 million. This approach goes beyond selecting alternative routes and provides decision makers with measurable benefits that justify diversion strategies.https://www.mdpi.com/2076-3417/14/22/10134alternative route selectioncongestion mitigationtruck diversion strategiestraffic managementGIS applications in transportation |
| spellingShingle | Samar Younes Amr Oloufa Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion Applied Sciences alternative route selection congestion mitigation truck diversion strategies traffic management GIS applications in transportation |
| title | Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion |
| title_full | Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion |
| title_fullStr | Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion |
| title_full_unstemmed | Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion |
| title_short | Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion |
| title_sort | applying topological information for routing commercial vehicles around traffic congestion |
| topic | alternative route selection congestion mitigation truck diversion strategies traffic management GIS applications in transportation |
| url | https://www.mdpi.com/2076-3417/14/22/10134 |
| work_keys_str_mv | AT samaryounes applyingtopologicalinformationforroutingcommercialvehiclesaroundtrafficcongestion AT amroloufa applyingtopologicalinformationforroutingcommercialvehiclesaroundtrafficcongestion |