Understanding taxi travel patterns

Taxis play important roles in modern urban transportation systems, especially in mega cities. While providing necessary amenities, taxis also significantly contribute to traffic congestion, urban energy consumption, and air pollution. Understanding the travel patterns of taxis is thus important for addressing many urban sustainability challenges. Previous research has primarily focused on examining the statistical properties of passenger trips, which include only taxi trips occupied with passengers. However, unoccupied trips are also important for urban sustainability issues because they represent potential opportunities to improve the efficiency of the transportation system. Therefore, we need to understand the travel patterns of taxis as an integrated system, instead of focusing only on the occupied trips. In this study we examine GPS trajectory data of 11,880 taxis in Beijing, China for a period of three weeks. Our results show that taxi travel patterns share similar traits with travel patterns of individuals but also exhibit differences. Trip displacement distribution of taxi travels is statistically greater than the exponential distribution and smaller than the truncated power-law distribution. The distribution of short trips (less than 30 miles) can be best fitted with power-law while long trips follow exponential decay. We use radius of gyration to characterize individual taxi’s travel distance and find that it does not follow a truncated power-law as observed in previous ∗ Corresponding authors. E-mail addresses: [email protected] (H. Cai), [email protected] (M. Xu). 1 Tel.: +1 765 494 7701; fax: +1 765 494 7704. 2 Tel.: +1 734 763 8644; fax: +1 734 936 2195. http://dx.doi.org/10.1016/j.physa.2016.03.047 0378-4371/© 2016 Elsevier B.V. All rights reserved. H. Cai et al. / Physica A 457 (2016) 590–597 591 studies. Spatial and temporal regularities exist in taxi travels. However, with increasing spatial coverage, taxi trips can exhibit dual high probability density centers. © 2016 Elsevier B.V. All rights reserved.