Panichpapiboon, Sooksan
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Panichpapiboon, Sooksan
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Email
sooksan.pa@kmitl.ac.th
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Item type:Publication, What Separates High-Performing Taxis From the Rest? A Case Study in Bangkok(2024-01-01)Taxi is a public transportation system widely used in many cities, including Bangkok, Thailand. It provides a convenient way for people to move around the city. However, past studies have shown that the Bangkok taxi system is highly inefficient. In fact, most taxis are vacant most of the time. Despite this fact, there are highly efficient taxis that outperform the others in terms of gaining higher revenue. Learning what these high-performing taxis do differently is essential to improving the overall system's efficiency. In this paper, we investigate the key factors that differentiate high-performing taxis from low-performing ones. Identifying these factors allows us to draw significant insights into improving each taxi's performance. Based on an analysis of real taxi trajectory data, this study shows that the two crucial factors that separate high-performing taxis from low-performing taxis are the passenger searching time and the ability to select less congested search routes. Thus, an effective solution needs to concentrate on improving these two factors. Enhancing other elements, such as passenger delivery time and delivery route, is much less effective and will not have any critical impact. Lastly, this paper presents an effective regression model for predicting the efficiency of an individual taxi based on its average vacant time and the proportion of time spent in congestion during a passenger search. The model performs well, with only an 8.28% error rate. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Big Data Analysis on Urban Mobility: Case of Bangkok(2022-01-01); Khunsri, KavepolDesigning an efficient on-demand mobility service requires comprehensive knowledge of the statistical characteristics of trips. In other words, it is critical to know how long passengers typically spend on a trip and how far they usually travel. Likewise, it is important to learn how much time a driver spends searching for passengers. This study presents a statistical analysis of taxi trips in Bangkok based on real traces of 5,853 taxis over the period of three months. Significant insights on trip volume, trip time, trip distance, and origin-destination distance are derived. In addition, the probability distributions of trip time, trip distance, and origin-destination distance are also characterized based on two goodness-of-fit tests. To our knowledge, this characterization is done for the first time for Bangkok taxi trips. It is shown that a lognormal distribution can best describe the empirical trip time distribution. On the other hand, a Weibull distribution can best describe the empirical trip distance distribution and the empirical origin-destination distance distribution. These distributions are essential to traffic simulation. Finally, the efficiency of the Bangkok taxi system is also quantified both at the system level and at the agent level.