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在活动计划的时空镜内访问概率和可访问性
Jing Lyu1, Feixiong Liao1, Soora Rasouli1
1Urban Planning and Transportation Group, Eindhoven University of Technology, Eindhoven, The Netherlands.
International journal of geographical information science : IJGIS
|April 16, 2025
概括
本研究引入了概率空间-时间镜 (STP) 以更好地测量可访问性,超越二进制假设. 新模型考虑了个体旅行差异,并提供了更全面的评估到达机会.
科学领域:
- 运输 地理 交通 地理
- 城市规划 城市规划
- 人类流动性研究 人类流动性研究
背景情况:
- 传统的时空镜 (STP) 模型经常使用二进制可访问性,假设镜内有平等的访问权限,没有外部访问权限.
- 现有的概率STP模型主要集中在旅行级别分析上,限制了它们在全面的可访问性测量中的应用.
- 在目前的STP框架中,旅行行为和活动参与的个体异质性没有得到充分的解决.
研究的目的:
- 为日常活动计划构建和估计概率空间-时间镜 (STP) 提出一种新型模型框架.
- 开发一个时空可访问性测量方法,将从概率性的STP中得出的访问概率纳入其中.
- 通过使用隐性类型模型来考虑旅行和活动参与中的个人异质性.
主要方法:
- 开发了一个基于多州超级网络的模型框架,以构建概率性的STP.
- 采用隐性类型模型来估计概率的STP,捕捉出行和活动参与的个体差异.
- 提出了一个新的时空可访问性测量方法,将从概率性STP中集成访问概率.
主要成果:
- 拟议的模型框架有效地构建和估计概率STP,在日常活动计划中捕捉细微的可访问性.
- 潜阶级模型成功地解释了个人在旅行和活动参与中的异质性.
- 访问概率模型准确地表示了概率的STP内部,并与现实世界的移动数据进行了验证.
结论:
- 与二进制模型相比,概率STP框架提供了更现实的可访问性表示.
- 拟议的时空可访问性测量提供了一个全面的机会访问评估,考虑活动链和个人行为.
- 这种方法增强了我们对个人如何在空间和时间中导航,以获得复杂城市环境中的机会的理解.
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