Abstract
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.
Highlights
In an oil painting series crafted in early 1897, a French painter Camille Pissarro recorded the urban life of boulevard Montmartre from February to April in which “carriages, omnibuses, people, between big trees and big houses”1 were “surveyed” from his hotel window
To conduct a systematic review of the advances of street life and pedestrian activity research in computational urban science, this study focuses on published peer-reviewed academic papers held within Scopus and the Web of Science
Columns 1 and 5 in Table 4 indicate a similar finding, except that the effect of gap time diminishes. It implies that a longer gap time of traffic increases the likelihood of jaywalking events but not necessarily increases the number of jaywalking pedestrians
Summary
In an oil painting series crafted in early 1897, a French painter Camille Pissarro recorded the urban life of boulevard Montmartre from February to April in which “carriages, omnibuses, people, between big trees and big houses” were “surveyed” from his hotel window. 1https://www.metmuseum.org/art/collection/search/437310 collected either passively by observations or actively through respondents’ direct participation. In view of this deluge of urban information and efforts in deciphering the underlying urban dynamics, several papers have reviewed the use of various emerging datasets in studying pedestrian-related behaviors. This paper contributes to the existing literature on pedestrian experience through a systematic review of the environment components, pedestrian behaviour, and smart data in different parts of the world. The limitations of using static environmental variables in analyzing pedestrian-crossing behaviour at road junctions only have (2021) 1:26 been overcome through a pedestrian jaywalking study that integrates different sources of smart data, including bus dashcam, GSV images, and crowd-sourced platforms. The results help to inform pedestrian-friendly design and contributes to the ultimate goal of walkable cities
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