A Mathematical Programming Model and a Firefly-Based Heuristic for Real-Time Traffic Signal Scheduling With Physical Constraints
Traffic congestion is one of the challenges that face urban cities’ planners. It affects the environment as it increases the emissions of CO2 and affects the logistics systems as it may increase the travel time of different vehicles. Scheduling traffic signals is one of the ways to solve...
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9536710/ |
| _version_ | 1819129593859145728 |
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| author | Hanaa Abohashima Amr Eltawil Mohamed Gheith |
| author_facet | Hanaa Abohashima Amr Eltawil Mohamed Gheith |
| author_sort | Hanaa Abohashima |
| collection | DOAJ |
| description | Traffic congestion is one of the challenges that face urban cities’ planners. It affects the environment as it increases the emissions of CO2 and affects the logistics systems as it may increase the travel time of different vehicles. Scheduling traffic signals is one of the ways to solve this problem. In the urban traffic signal scheduling problem, it is desired to get the optimum schedule for each considered traffic signal to maximize or minimize a specific objective function(s); these schedules determine the active and inactive traffic phases during each cycle time. In this paper, a mathematical programming model for solving the urban traffic signal scheduling problem is presented, the proposed mathematical model captures the physical constraints of the problem. Furthermore, a firefly-based rolling horizon approach is proposed to solve the problem. Both methods are used to solve a traffic-responsive system, which is considered the future of traffic control systems. The performance of both methods has been simulated using the SUMO traffic simulator to verify the solutions. The performance of the solutions was measured using the average queue length of the roads, the average waiting time, and the average travel time. The proposed methods have been applied to a real case study, and the results were remarkable. |
| first_indexed | 2024-12-22T08:46:11Z |
| format | Article |
| id | doaj.art-35746363c05b4a8fbc96330b1407192a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T08:46:11Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-35746363c05b4a8fbc96330b1407192a2022-12-21T18:32:06ZengIEEEIEEE Access2169-35362021-01-01912831412832710.1109/ACCESS.2021.31126009536710A Mathematical Programming Model and a Firefly-Based Heuristic for Real-Time Traffic Signal Scheduling With Physical ConstraintsHanaa Abohashima0https://orcid.org/0000-0001-5178-1968Amr Eltawil1Mohamed Gheith2https://orcid.org/0000-0003-2092-2697Department of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology, Alexandria, EgyptDepartment of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology, Alexandria, EgyptDepartment of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology, Alexandria, EgyptTraffic congestion is one of the challenges that face urban cities’ planners. It affects the environment as it increases the emissions of CO2 and affects the logistics systems as it may increase the travel time of different vehicles. Scheduling traffic signals is one of the ways to solve this problem. In the urban traffic signal scheduling problem, it is desired to get the optimum schedule for each considered traffic signal to maximize or minimize a specific objective function(s); these schedules determine the active and inactive traffic phases during each cycle time. In this paper, a mathematical programming model for solving the urban traffic signal scheduling problem is presented, the proposed mathematical model captures the physical constraints of the problem. Furthermore, a firefly-based rolling horizon approach is proposed to solve the problem. Both methods are used to solve a traffic-responsive system, which is considered the future of traffic control systems. The performance of both methods has been simulated using the SUMO traffic simulator to verify the solutions. The performance of the solutions was measured using the average queue length of the roads, the average waiting time, and the average travel time. The proposed methods have been applied to a real case study, and the results were remarkable.https://ieeexplore.ieee.org/document/9536710/Firefly heuristicmathematical programmingrolling horizontraffic signal schedulingtransportation |
| spellingShingle | Hanaa Abohashima Amr Eltawil Mohamed Gheith A Mathematical Programming Model and a Firefly-Based Heuristic for Real-Time Traffic Signal Scheduling With Physical Constraints IEEE Access Firefly heuristic mathematical programming rolling horizon traffic signal scheduling transportation |
| title | A Mathematical Programming Model and a Firefly-Based Heuristic for Real-Time Traffic Signal Scheduling With Physical Constraints |
| title_full | A Mathematical Programming Model and a Firefly-Based Heuristic for Real-Time Traffic Signal Scheduling With Physical Constraints |
| title_fullStr | A Mathematical Programming Model and a Firefly-Based Heuristic for Real-Time Traffic Signal Scheduling With Physical Constraints |
| title_full_unstemmed | A Mathematical Programming Model and a Firefly-Based Heuristic for Real-Time Traffic Signal Scheduling With Physical Constraints |
| title_short | A Mathematical Programming Model and a Firefly-Based Heuristic for Real-Time Traffic Signal Scheduling With Physical Constraints |
| title_sort | mathematical programming model and a firefly based heuristic for real time traffic signal scheduling with physical constraints |
| topic | Firefly heuristic mathematical programming rolling horizon traffic signal scheduling transportation |
| url | https://ieeexplore.ieee.org/document/9536710/ |
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