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• W3162300915 abstract "In the urban traffic research field, taxi detour behavior analysis can be regarded as one of the most crucial and challenging topics accounting for real-world routing network dynamics with complicated external inducement such as “avoiding congestion sections”, “unfamiliarity with road maps” or just “earning more fee under a longer travel path”. We carried out an interdisciplinary research framework to build a more holistic and profound view of the spatio-temporal distribution of the taxi detour behavior at directional road segment (DRS) level. First, a map matching based detour clustering method was proposed to deal with one week of taxi GPS tracing (divided into 3.4 million occupied trips). Then we employed an established multi-layer road index system in Shenzhen, China, to illustrate the spatio-temporal distribution variation of taxi detour features and statistics. Furthermore, three categories of DRS factors related to road structural attributes, traffic dynamics and point-of-interests (POIs) were defined to fit a selected-sample-based binary logit model. Some remarkable findings include: (i) in Shenzhen on average, 23.5 percent of taxi trips made a detour larger than 2.1 kilometers, which could be astonishingly high considering that only a very few trips yielded formal complaints for fraudulent detouring; (ii) both the level of detour intensity and ratio are affected by road features and dynamics in different spatio-temporal interaction patterns." @default.
• W3162300915 created "2021-05-24" @default.
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• W3162300915 date "2022-07-01" @default.
• W3162300915 modified "2023-10-14" @default.
• W3162300915 title "Mining Factors Affecting Taxi Detour Behavior From GPS Traces at Directional Road Segment Level" @default.
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• W3162300915 doi "https://doi.org/10.1109/tits.2021.3074976" @default.
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