Optimization Design of Expressway Traffic Flow Guidance System Based on GIS and Improved Ant Colony Optimization Algorithms
Although the total number of highway traffic kilometers in China is increasing, it is still difficult to meet the needs of rapid economic development. The large influx of traffic has increased the pressure on highways, and traffic congestion often occurs, greatly affecting road safety and the effici...
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| Veröffentlicht in: | 2023 International Conference on Telecommunications, Electronics and Informatics (ICTEI) S. 71 - 75 |
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| Hauptverfasser: | , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
11.09.2023
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| Schlagworte: | |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | Although the total number of highway traffic kilometers in China is increasing, it is still difficult to meet the needs of rapid economic development. The large influx of traffic has increased the pressure on highways, and traffic congestion often occurs, greatly affecting road safety and the efficiency of traffic flow. In this regard, this article integrates GIS and improved ACA (Ant Colony Algorithm) to optimize the design of highway traffic flow guidance system. The research shows that when the number of ants is different, it has a certain impact on the Rate of convergence of the algorithm. When the number of ants \mathrm{m}=60, the algorithm does not converge to the same solution. When the number of ants is 60, 80, and 100, the solution time of the algorithm is 4.2890 \mathrm{~s}, 6.78 \mathrm{~s}, 6.64 \mathrm{~s}, and 6.14 \mathrm{~s}, respectively. It can be seen that as the number of ants increases, the solving time will also increase. The optimized traffic flow guidance system utilizes GIS to ensure smooth, fast, and safe driving of vehicles on highways, keeping them in the optimal driving environment. GIS can help improve the efficiency of traffic and road safety, and maintain harmony and unity among vehicles, roads, and people. |
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| DOI: | 10.1109/ICTEI60496.2023.00104 |