基于YOLOv5的行人流动模拟的社会力量模型的参数校准
Tianle Li1, Bingbing Xu1, Weike Lu1
1School of Rail Transportation, Soochow University, Suzhou 215000, China.
Sensors (Basel, Switzerland)
|August 10, 2024
概括
这项研究使用YOLOv5.5校准了行人流动模拟模型. 改进的模型准确地复制了现实世界地铁站的行人行为,减少了模拟错误.
科学领域:
- 城市规划和交通科学 城市规划和交通科学
- 计算社会科学 计算社会科学
- 交通工程是交通工程.
背景情况:
- 地铁系统对于城市交通至关重要,需要准确的行人流量模拟,以确保安全和管理.
- 目前的模拟模型需要与真实世界的数据进行校准,以增强现实性.
- 现有的方法往往在模拟和实际行人行为之间产生重大差异.
研究的目的:
- 开发和验证地铁站的行人流量模拟模型的校准方法.
- 通过使用现实世界的行人流动数据来提高社会力量模型的准确性.
- 缩小交通环境中模拟和实际行人动态之间的差距.
主要方法:
- 利用YOLOv5进行行人检测和跟踪,以收集真实世界的流量数据.
- 在Anylogic中应用了校准方法来优化社会力量模型中的参数.
- 将模拟输出与收集的真实世界数据进行比较,以评估模型性能.
主要成果:
- 校准的模型参数成功地重现了地铁站行人流动的关键特征.
- 校准方法显著减少了整体模拟错误.
- 这种方法减轻了模拟结果与现实之间存在重大差异的常见问题.
结论:
- 基于YOLOv5的校准方法提高了地铁环境中行人流动模拟的可靠性.
- 精确的模拟对于有效的站点管理和风险评估至关重要.
- 这种方法为改善行人流量模型的预测能力提供了可靠的工具.
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