Taxi is an indispensable mode in the urban public transportation. Although many studies have explored the travel patterns of taxi trips, few have combined taxi and subway to reveal their intermodal relationship. To bridge the gap, this study utilized taxi's trajectory data to investigate its relationship with subway. Considering the multifaceted relationship between taxi and subway in operation, taxi trips are categorized into three types, namely, subway-competing, subway-extending, and subwaycomplementing taxi trips. The characteristics of each type of taxi trips reflect the specialties and their interactions with subway. The origin/destination distributions of taxi and subway trips are compared and analyzed. Furthermore, the supply and demand of taxi within the buffer zone of each subway station are analyzed to reflect the difficulty of hailing taxis. The negative binomial regression models are used to explore the relationship between taxi trips and subway ridership. The results show that there is a significantly positive correlation between taxi trips and subway ridership.

Accessibility has drawn extensive attention from city planners and transportation researchers for decades. With the benefits of large-scale and varying time, this study aims to combine the taxi global positioning system (GPS) data with a cumulative opportunity measure to calculate taxi accessibility in Beijing, China. As traffic conditions vary significantly over time and space, we select four typical time periods and introduce a grid-based method to divide the study area into grid cells. Both the GPS signals and opportunities that include the constant points of interest, total drop-offs, and dynamic drop-offs, are aggregated in these grid cells. The cumulative opportunity measure counts all reachable grid cells within the given travel time threshold, along with the corresponding opportunities. The results demonstrate that the accessibility varies in the four time periods, with better performance seen in the late-night hours. Although the spatial distributions of the three kinds of opportunities are different, these accessibilities show great similarity. In addition, the relative accessibilities of different measures are highly correlated. In general, grid cells with higher accessibilities in one time period are likely to also have higher accessibilities in other time periods. Moreover, the results suggest that taxi accessibility can be measured from its trajectory data only.

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The normal studies on air traffic departure scheduling problem (DSP) mainly deal with an independent airport in which the departure traffic is not affected by surrounded airports, which, however, is not a consistent case. In reality, there still exist cases where several commercial airports are closely located and one of them possesses a higher priority. During the peak hours, the departure activities of the lower-priority airports are usually required to give way to those of higher-priority airport. These giving-way requirements can inflict a set of changes on the modeling of departure scheduling problem with respect to the lower-priority airports. To the best of our knowledge, studies on DSP under this condition are scarce. Accordingly, this paper develops a bi-objective integer programming model to address the flight departure scheduling of the partly-restricted (e.g., lower-priority) one among several adjacent airports. An adapted tabu search algorithm is designed to solve the current problem. It is demonstrated from the case study of Tianjin Binhai International Airport in China that the proposed method can obviously improve the operation efficiency, while still realizing superior equity and regularity among restricted flows.

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