Fan Zhuangyuan, Loo Becky P Y
Department of Geography, University of Hong Kong, School of Geography and Environment, Jiangxi Normal University, Nanchang, China.
Comput Urban Sci. 2021;1(1):26. doi: 10.1007/s43762-021-00024-9. Epub 2021 Nov 27.
Ongoing efforts among cities to reinvigorate streets have encouraged innovations in using smart data to understand pedestrian activities. Empowered by advanced algorithms and computation power, data from smartphone applications, GPS devices, video cameras, and other forms of sensors can help better understand and promote street life and pedestrian activities. Through adopting a pedestrian-oriented and place-based approach, this paper reviews the major environmental components, pedestrian behavior, and sources of smart data in advancing this field of computational urban science. Responding to the identified research gap, a case study that hybridizes different smart data to understand pedestrian jaywalking as a reflection of urban spaces that need further improvement is presented. Finally, some major research challenges and directions are also highlighted.
城市为振兴街道所做的持续努力，推动了利用智能数据理解行人活动方面的创新。借助先进算法和计算能力，来自智能手机应用程序、全球定位系统设备、摄像机及其他形式传感器的数据，有助于更好地理解和促进街道生活及行人活动。本文采用以行人为导向、基于场所的方法，回顾了推进这一计算城市科学领域的主要环境要素、行人行为及智能数据来源。针对已识别的研究空白，本文呈现了一个案例研究，该研究将不同的智能数据进行整合，以理解行人乱穿马路现象，将其作为城市空间有待进一步改善的一种反映。最后，还强调了一些主要的研究挑战和方向。
