针对车辆管理系统的有效路径检测和拥堵避免的异质算法
Melaouene Noussaiba1, Abdul Razaque2, Romadi Rahal1
1Team of Information Research and Indexing Documents, Texts and Multimedia, ENSIAS, Mohammad V University, Rabat BP 713, Morocco.
Sensors (Basel, Switzerland)
|July 8, 2023
概括
本研究介绍了ACO-PT,这是一种用于智能城市交通管理的新算法. 它提高了有效的路由,降低了能源消耗,并改善了城市环境中的数据吞吐量.
科学领域:
- 计算机科学 计算机科学
- 运输工程 运输工程
- 人工智能的人工智能
背景情况:
- 超大城市的交通拥堵是一个持续的问题,人口和车辆增长加剧了这一问题.
- 现有的路由算法需要提高效率,能源使用和延迟.
- 智慧城市计划,特别是汽车互联网 (IoV),提供了潜在的解决方案.
研究的目的:
- 为城市交通管理开发一个高效的路由算法.
- 为了提高能源效率,增加数据吞吐量,减少端到端延迟.
- 为了解决车辆拥堵问题,并增强自动车辆检测.
主要方法:
- 一个异质的算法,殖民地优化与Pheromone白 (ACO-PT),是开发的.
- ACO-PT集成了殖民地优化 (ACO) 和费洛蒙白 (PT) 算法.
- 一个避免拥堵的模块和一个自动车辆检测 (AVD) 模块被纳入.
主要成果:
- 在实验模拟中,ACO-PT算法表现出卓越的性能.
- 与三个最先进的算法相比,ACO-PT显示了显著的改进.
- 提高了关键性能指标:能源使用,端到端延迟和吞吐量.
结论:
- 拟议的ACO-PT算法有效地解决了城市地区的高效路由问题.
- ACO-PT为缓解交通拥堵和改进 IoV 系统提供了一个有前途的解决方案.
- 该算法在能源效率,延迟和吞吐量方面的改进验证了它的有效性.
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