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Updated: Jan 19, 2026

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Trajectory Data Analyses for Pedestrian Space-time Activity Study
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推断一个交通枢纽的行人流动结构
Xiaolu Jia1, Claudio Feliciani2, Hisashi Murakami3
1Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China.
Accident; analysis and prevention
|January 17, 2026
概括
这项研究引入了一种新的模型,以了解繁忙的交通枢纽中的行人运动,提高安全性和效率. 该模型准确地预测出发目的地需求和路线选择,有助于有效地管理拥堵.
科学领域:
- 运输科学 运输科学
- 复杂系统建模 复杂系统建模
- 城市规划 城市规划
背景情况:
- 交通枢纽中的行人流量会形成复杂的网络,导致高峰时段的交通拥堵.
- 现有的模型往往侧重于微观相互作用,忽视了宏观的来源-目的地 (OD) 需求和中观路线选择.
研究的目的:
- 开发和验证交通枢纽的综合战略战术运营 (STO-Hub) 模型.
- 解决大型设施中行人动态的战略和战术建模方面的差距.
主要方法:
- 从JR新宿站的11个LiDAR传感器中利用了0.87万个行人轨迹.
- 采用重力模型进行战略性OD需求估计.
- 在战术路线选择行为中使用logit模型.
- 实施了一个基于代理的模型,用于操作交互.
主要成果:
- 该STO-Hub模型准确地重建了OD需求和路线选择行为.
- 与定向流量计数和划定拥堵区域达成高度一致.
- 在战略,战术和操作层面上成功捕获了行人动态.
结论:
- STO-Hub模型为了解和管理交通枢纽的行人流动提供了经过验证的框架.
- 综合方法支持OD知情的行人指导,拥堵预防和提高运营效率.
- 该研究为枢纽管理提供了一个实用的10分钟解析基础.
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