Tempo-spatial analysis of pedestrian movement in the built environment based on crowdsourced big data

Abstract

Over the years, the urban planning literature has focused substantial attention on walkability research, aiming to enhance physical activity and sustainable communities through urban planning and design. While motorized traffic research has gained momentum in combining innovative technologies for traffic monitoring, the common tools used to monitor pedestrian movement (PM) to this date are limited in time and scale. This study aims at analyzing tempo-spatial dynamics of walking behavior, while utilizing an emerging technology of Bluetooth sensors. We analyzed over 53 million pedestrian records, monitored in 83 street-segments in Tel-Aviv, Israel. The data was recorded for five months, including the time of COVID-19's first lockdown. We showcase tempo-spatial dynamics of PM through different times of the year, while discussing changes in walking traffic volume, walking patterns (frequency peaks), traffic at commercial vs. residential streets, popular street segments and land-uses, and possible applications to urban planning and design. Finally, we discuss the data limitations and challenges for PM monitoring and research. The study shows that BT sensor technology can provide the municipality and decisionmakers with insights on pedestrians' behavior and preferences in real-time and at street-level, enabling to locate infrastructure investments more efficiently and to support planning decisions. The preliminary results of this study suggest further use of this technology for pedestrian movement monitoring and research in urban networks.

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