2017
DOI: 10.1371/journal.pone.0183574
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The impact of rainfall on the temporal and spatial distribution of taxi passengers

Abstract: This paper focuses on the impact of rainfall on the temporal and spatial distribution of taxi passengers. The main objective is to provide guidance for taxi scheduling on rainy days. To this end, we take the occupied and empty states of taxis as units of analysis. By matching a taxi's GPS data to its taximeter data, we can obtain the taxi's operational time and the taxi driver's income from every unit of analysis. The ratio of taxi operation time to taxi drivers' income is used to measure the quality of taxi p… Show more

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Cited by 12 publications
(9 citation statements)
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References 29 publications
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“…This could be explained by the fact that discretionary passengers are more affected by rain than 635 commuters (Changnon, 1996), i.e., people are obliged to go out for their daily duties on weekdays and therefore might adapt their travel modes, while on weekends they can opt to stay at home under heavy rain. In addition, similarly to what Chen et al (2017) found when studying the impact of rainfall on taxi use, we also found a trend of more vehicular use under rainy weather, and less walking in heavier rain.…”
supporting
confidence: 87%
“…This could be explained by the fact that discretionary passengers are more affected by rain than 635 commuters (Changnon, 1996), i.e., people are obliged to go out for their daily duties on weekdays and therefore might adapt their travel modes, while on weekends they can opt to stay at home under heavy rain. In addition, similarly to what Chen et al (2017) found when studying the impact of rainfall on taxi use, we also found a trend of more vehicular use under rainy weather, and less walking in heavier rain.…”
supporting
confidence: 87%
“…Other exogenous factors, such as inclement weather can affect short-term demand differently by mode, as noted in the case of road traffic (Thakuriah and Tilahun 2013), public transport (Tang and Thakuriah 2012), and bicycling (Meng et al 2016). The significant relationship of inclement weather to taxi use (Chen et al 2017) and ride-hailing (Brodeur and Nield 2017) has also been pointed out. Other long-term socio-economic factors, for example, income levels or employment activity, can also affect travel demand.…”
Section: The Ride-hailing Short-term Demand Forecasting Problemmentioning
confidence: 94%
“…These travel times for ride-sharing programs are also affected by weather. For example, Chen et al [2017] showed that taxi demand decreased with rainfall during non-rush hours but increased with rainfall during rush hours. As a result, both the probability of a real request and the times to serve will be influenced by weather conditions.…”
Section: Practical Implicationsmentioning
confidence: 99%