Using simple agent-based modeling to inform and enhance neighborhood walkability.
Using simple agent-based modeling to inform and enhance neighborhood walkability.
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DOI：
10.1186/1476-072x-12-58
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发表时间：
2013-12-11
影响因子：
4.9
通讯作者：
Giles-Corti B
中科院分区：
文献类型：
--
作者：
Badland H;White M;Macaulay G;Eagleson S;Mavoa S;Pettit C;Giles-Corti B
步行友好型社区具有近距离的目的地和服务，鼓励步行，减少对汽车的依赖，从而有助于建立更活跃、更健康的社区。靠近主要目的地和服务是城市设计决策过程的一个重要方面，特别是在采用交通导向发展（TOD）方法进行城市规划的地区，即在交通节点的步行距离内发生密度。社区内的目的地访问建模仅限于圆形集水区缓冲区或使用地理信息系统（GIS）中的地理处理例程生成的更复杂的网络缓冲区。循环和网络缓冲集水法都有问题。圆形集水区模型没有考虑到街道网络，因此不允许探索性的“假设”情景建模；和网络缓冲功能通常存在于专有的GIS软件中，这些软件可能成本高昂，并且需要高水平的专业知识才能操作。本研究试图通过开发一个开源的、简单的基于智能体的可步行集水区工具来克服这些限制，该工具可被研究人员、城市设计师、规划者和政策制定者用于测试改善社区可步行集水区的方案。使用来自澳大利亚城市研究基础设施网络（AURIN）的数据，将基于代理的模型的简化版本移植到基于矢量的开源GIS网络工具中。该工具是根据最终用户利益相关者工作组的意见开发和测试的。由此产生的模型已被证明是有效和灵活的，允许利益相关者评估和优化社区集水区在实际或潜在感兴趣的节点（例如，学校，公共交通站点）周围的可步行性。用户可以派生一系列度量来比较不同的建模场景。这些包括：集水区面积与循环缓冲比率；横过街道的平均数目；以及不同步行速度和路口等待时间的建模。该工具有能力影响规划和公共卫生宣传与实践，并且通过使用开放获取的源代码软件，可在当地和国际上使用。这个版本的工具也可以从一个简单的模型扩展到一个复杂的模型，其中包括代理（即模拟行人）“学习”，并结合其他环境属性来提高步行性（例如，住宅密度、混合土地使用、交通量）。
Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory ‘what-if’ scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate. This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input. The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and modeling of different walking speeds and wait time at intersections. The tool has the capacity to influence planning and public health advocacy and practice, and by using open-access source software, it is available for use locally and internationally. There is also scope to extend this version of the tool from a simple to a complex model, which includes agents (i.e., simulated pedestrians) ‘learning’ and incorporating other environmental attributes that enhance walkability (e.g., residential density, mixed land use, traffic volume).