Understanding the spatial variation of taxi ridership is of critical importance to many government agencies and taxi companies because taxis’ location dependency on spatial pattern of passenger demand results in spatially unbalanced taxi demand and supply. This study presents an analysis of the spatial distribution of taxi ridership by using large-scale GPS taxi trip data collected from Seoul, South Korea. To capture the spatial variations better in taxi ridership, GPS entities were disaggregated into units of a uniform size with a grid cell decomposition method. A geographically weighted spatial regression was applied to model spatial correlations of factors associated with transit and urban density to taxi ridership. Results from the proposed method demonstrated a higher relationship between taxi and subway ridership in the regions where lower accessibility to subway stations existed. In these regions, taxis were found to perform as a complementary mode to subway. In residential and commercial districts, this analysis showed that population and employment were highly related to taxi ridership. In contrast, in central business districts it was the building area (floor space), rather than population and employment, that was highly related to taxi ridership.

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Understanding truck activity is an essential component of strategic freight planning and programming. However, recent studies have revealed a significant void in the availability of detailed truck activity data. Although some existing detectors are capable of providing truck counts by axle configuration, higher-resolution data that indicate truck body configuration, industry served, and commodity carried cannot be obtained from existing sensors. This paper presents the newly developed Truck Activity Monitoring System, which leverages existing in-pavement traffic sensors to provide truck activity data in California. Existing inductive loop detector sites were updated with inductive signature technology and advanced truck classification models were implemented to provide detailed truck count data with more than 40 truck body configurations. The system has been deployed to more than 90 detector locations in California to provide coverage at state borders, regional cordons, and significant metropolitan truck corridors. An interactive geographic information system website provides users with advanced visual analytics and access to archived data across all deployed locations. The case studies presented in this paper demonstrate the potential of the data obtained from this system in analyzing and understanding current and historical industry-specific truck activity.