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Introducing shared life experience metric in urban planning
Transportation ( IF 3.5 ) Pub Date : 2020-02-25 , DOI: 10.1007/s11116-020-10087-y
Mahdieh Allahviranloo , Thomas Bonet , Jérémy Diez

Historically cities are formed to provide interaction and communication opportunities for communities. As cities become smarter, new forms of interactions are formed and the necessity to participate in activities such as traveling to a grocery store is replaced by submission of online order in Amazon fresh. If we move in this direction, it bears answering the question of what kinds of societal loss, or changes in social interactions should we expect in our future cities? In this paper, we develop the Shared Life Experience (SLE) metric, focusing on the interaction opportunities between people. We define this metric to be measured based on the pairwise reachability and interaction probabilities of city dwellers in the context of time and space. Furthermore, we present a framework discussing how this metric can be embedded into the design of a more dynamic urban form and how we can measure it using publicly available data. Two sets of analyses are presented. First : a bi-level model is proposed, composed of a heuristic search algorithm in the upper level to estimate the regional SLE value for a given set of parameters and finding the optimum solution. The lower level models in the bi-level structure are activity-based models producing mobility behavior of individuals in response to changes in the input parameters. Second : we present a simple methodology and discuss how to quantify the SLE index using household travel survey data collected within five boroughs of New York City. This analysis can highlight many equity-related objectives and be used as an informative tool for better decision making.

中文翻译:

在城市规划中引入共享生活体验指标

从历史上看,城市的形成是为了为社区提供互动和交流的机会。随着城市变得更加智能,新的互动形式形成,参加诸如前往杂货店之类的活动的必要性被在亚马逊生鲜中提交在线订单所取代。如果我们朝着这个方向前进,那么我们应该在未来的城市中期待什么样的社会损失或社会互动的变化?在本文中,我们开发了共享生活体验 (SLE) 指标,重点关注人与人之间的互动机会。我们根据城市居民在时间和空间的背景下的成对可达性和交互概率来定义这个度量标准。此外,我们提出了一个框架,讨论如何将这个指标嵌入到更具活力的城市形态的设计中,以及我们如何使用公开可用的数据对其进行衡量。提出了两组分析。第一:提出了一个双层模型,由上层的启发式搜索算法组成,用于估计给定参数集的区域 SLE 值并找到最佳解决方案。双层结构中的低层模型是基于活动的模型,产生个体响应输入参数变化的移动行为。第二:我们提出了一种简单的方法,并讨论如何使用在纽约市五个行政区收集的家庭旅行调查数据来量化 SLE 指数。这种分析可以突出许多与公平相关的目标,并可用作做出更好决策的信息工具。
更新日期:2020-02-25
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