ABSTRACT Pedestrian movement in the built environment has attracted research foci from both urban planning and transportation. Characteristics of built environment, such as urban forms, road network system, and building layout, can affect people’s movement in different space. Thus, the quality of the space becomes measurable through evaluating people’s movement for design/planning purpose. Nowadays, the built environment is becoming more complex, in which the exterior and interior space are integrated to form a multilevel network. Studying the pedestrian movement in those areas can deepen the understanding toward the mechanism of people’s route choice, and provide useful insights for both spatial design and urban planning. The objective of this study is to construct a model which can map the pedestrian flow in the station complex buildings. The space syntax and SNA (Social network analysis) methodologies are adopted to investigate people’s movement in the built environment with integrated exterior and interior space. The station complex buildings of Tuen Mum station, Hong Kong is selected as case study. The network that connecting the station and surrounding function areas (within walkable distance) is consists of road system, bridges, and interior passageways. The indexes that evaluating the network characteristics, such as integration in space syntax and centralities in SNA will be calculated and compared. The modelling results will be validated by the on-site survey. The accomplished model can be used as a practical tool in designing complex space at metro station catchment area.摘要建筑环境中的行人运动一直是城市规划界和城市规划界的研究热点还有交通。建成环境的特征,如城市形态、路网系统,而建筑布局,会影响人们在不同空间的运动。因此,空间的质量通过评估设计/规划目的的人员流动而变得可测量。如今,建筑环境越来越复杂,室内外空间越来越复杂形成多级网络。对这些地区行人运动的研究可以深化对人的路径选择机制的认识,为我们提供有益的启示空间设计和城市规划。本研究的目的是建立一个可以绘制车站综合楼内的人流图。空间句法与社会网络分析)方法学被用来研究人们在建筑环境中的运动整合的外部和内部空间。香港屯门车站综合楼本文选取了孔作为研究对象。连接车站与周边功能的网络区域(可步行距离内)由道路系统、桥梁和内部通道组成。这个评价网络特性的指标,如空间句法整合度和中心度将计算和比较SNA中的。模拟结果将通过现场调查进行验证。该模型可作为地铁车站复杂空间设计的实用工具集水区。
2021-02-02REFERENCES Antonini, G., Bierlaire, M., & Weber, M. (2006). Discrete choice models of pedestrian walking behavior, 40, 667–687. https://doi.org/10.1016/j.trb.2005.09.006 Chen, J., & Chang, Z. (2015). Rethinking urban green space accessibility: evaluating and optimizing public transportation system through social network analysis in megacities.150–159. https://doi.org/10.1016/j.landurbplan.2015.07.007 Clifton, K. J., Singleton, P. A., Muhs, C. D., & Schneider, R. J. (2016). Development of destination choice models for pedestrian travel. 255–265. https://doi.org/10.1016/j.tra.2016.09.017 Duncan, D. T., Aldstadt, J., Whalen, J., & Melly, S. J. (2011). Validation of Walk Score ® for Estimating Neighborhood Walkability : An Analysis of Four US Metropolitan Areas, 4160– 4179. https://doi.org/10.3390/ijerph8114160 Ewing, R., Handy, S., Ewing, R., & Handy, S. (2009). Measuring the Unmeasurable : Urban Design Qualities Related to Walkability Measuring the Unmeasurable : Urban Design Qualities, 4809. https://doi.org/10.1080/13574800802451155 Foltˆ, J., & Piombini, A. (2007). Urban layout , landscape features and pedestrian usage, 81, 225–234. https://doi.org/10.1016/j.landurbplan.2006.12.001Frank, L. D., Sallis, J. F., Conway, T. L., Chapman, J. E., Saelens, B. E., Bachman, W., … James, E. (2007). Many Pathways from Land Use to Health, https://doi.org/10.1080/01944360608976725 Hillier, B. (n.d.). Iacono, M., Krizek, K. J., & El-geneidy, A. (2010). Measuring non-motorized accessibility : issues , alternatives , and execution. (1), 133–140. https://doi.org/10.1016/j.jtrangeo.2009.02.002 Jonathan Solomon. (2012).Kong, F., Yin, H., Nakagoshi, N., & Zong, Y. (2010). Landscape and Urban Planning Urban green space network development for biodiversity conservation : Identification based on graph theory and gravity modeling, , 16–27. https://doi.org/10.1016/j.landurbplan.2009.11.001 Lerman, Y., Rofè, Y., & Omer, I. (2014). Using Space Syntax to Model Pedestrian Movement in Urban Transportation Planning, 392–410. https://doi.org/10.1111/gean.12063 Liu, S., & Zhu, X. (2004). Accessibility Analyst : an integrated GIS tool for accessibility analysis in urban transportation planning.(1), 105– 124. https://doi.org/10.1068/b305 Manaugh, K., & El-geneidy, A. (2011). Validating walkability indices : How do different households respond to the walkability of their neighborhood ?(4), 309– 315. https://doi.org/10.1016/j.trd.2011.01.009 Nassir, N., Hickman, M., Malekzadeh, A., & Irannezhad, E. (2016). A utility-based travel impedance measure for public transit network accessibility, 26–39. https://doi.org/10.1016/j.tra.2016.03.007 Ozbil, A. (2017). Modeling street connectivity and pedestrian movement according to standard gis street network representations 018, (October). Porta, S., Crucitti, P., & Latora, V. (2006a). The network analysis of urban streets : A dual approach. 853–866. https://doi.org/10.1016/j.physa.2005.12.063 Porta, S., Crucitti, P., & Latora, V. (2006b). The Network Analysis of Urban Streets: A Primal Approach. (5), 705–725. https://doi.org/10.1068/b32045 Robin, T., Antonini, G., Bierlaire, M., & Cruz, J. (2009). Specification , estimation and validation of a pedestrian walking behavior model.(1), 36–56. https://doi.org/10.1016/j.trb.2008.06.010 Ryu, S., Chen, A., & Choi, K. (2017). Solving the combined modal split and traffic assignment problem with two types of transit impedance function.(3), 870–880. https://doi.org/10.1016/j.ejor.2016.08.019 Seyfried, A., Steffen, B., Klingsch, W., & Maik Boltes. (2005). The fundamental diagram of pedestrian movement revisited. (10), P10002. https://doi.org/10.1088/1742-5468/2005/10/P10002 Sheikh, A., Zadeh, M., & Rajabi, M. A. (2013). Analyzing the effect of the street network configuration on the efficiency of an urban transportation system., 285–297. https://doi.org/10.1016/j.cities.2012.08.008 Teklenburg, J. A. F., & Timmermans, H. J. P. (1993). Space syntax : standardised integration measures and, 20(March 1991), 347–357. Trasberg, T., Cheshire, J., & Longley, P. (2018). Integrating New Measures of Retail Unit Attractiveness into Spatial Interaction Models, 1–6.Vieira, A. P. (2012). Scaling relative asymmetry in space syntax analysis, (December). Wang, W. L., Lo, S. M., Liu, S. B., & Kuang, H. (2014). Microscopic modeling of pedestrian movement behavior : Interacting with visual attractors in the environment. 21–33. https://doi.org/10.1016/j.trc.2014.03.009 Zhong, C., Arisona, S. M., Huang, X., Batty, M., Schmitt, G., Zhong, C., … Batty, M. (2014). Detecting the dynamics of urban structure through spatial network analysis. (11), 2178–2199. https://doi.org/10.1080/13658816.2014.914521 Zhuang, Y., & Yao, Y. (2016). Commercial Space Use and Walking Path in Metro Station Areas of Shanghai Sub-Center. 85–88,117.
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