Early Birds, Night Owls,and Tireless/Recurring Itinerants: An Exploratory Analysis of Extreme Transit Behaviors in Beijing, China
Ying Long, Xingjian Liu, Jiangping Zhou, Yanwei Chai

TL;DR
This study analyzes extreme transit behaviors in Beijing, identifying patterns of early, late, long-distance, and frequent travelers using Smart Card Data and household surveys to inform urban planning.
Contribution
It introduces a combined approach using Smart Card Data and household surveys to profile and understand extreme transit behaviors in Beijing.
Findings
Identified spatiotemporal patterns of extreme transit behaviors.
Profiled socioeconomic backgrounds of extreme travelers.
Provided insights for urban transit planning and policy.
Abstract
This paper seeks to understand extreme public transit riders in Beijing using both traditional household survey and emerging new data sources such as Smart Card Data (SCD). We focus on four types of extreme transit behaviors: public transit riders who (1) travel significantly earlier than average riders (the 'early birds'); (2) ride in unusual late hours (the 'night owls'); and (3) commute in excessively long distance (the 'tireless itinerants'); (4) travel over frequently in a day (the 'recurring itinerants). SCD are used to identify the spatiotemporal patterns of these three extreme transit behaviors. In addition, household survey data are employed to supplement the socioeconomic background and provide a tentative profiling of extreme travelers. While the research findings are useful to guide urban governance and planning in Beijing, the methods developed in this paper can be applied…
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Taxonomy
TopicsUrban Transport and Accessibility · Human Mobility and Location-Based Analysis · Transportation Planning and Optimization
