Identifying the Temporal Characteristics of Intra-City Movement Using Taxi Geo-Location Data

Identifying the Temporal Characteristics of Intra-City Movement Using Taxi Geo-Location Data

Wenbo Zhang, Xinwu Qian, Satish V. Ukkusuri
DOI: 10.4018/978-1-5225-0827-4.ch004
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In this chapter, the authors focus on temporal patterns of urban taxi trips and explore determinant factors in conjunction with geodatabase at aggregate level. Zero-Inflated Negative Binomial model is proposed in light of count data nature and excessive number of O-D pairs with zero trip. Three typical time slots on weekdays, as well as weekends, are introduced as case study to check temporal variations of intra-city movement. The results indicate that trip distance, land use, socioeconomics, and built environment are significant variables that affect the number of taxi trips between two locations. In particular, longer travel and worse economy conditions, such as low employment and average annual income and more population under poverty, may prevent more movements, which have more impacts during peak hours. A better transit system may reduce the taxi trips, except for areas with more subway stations. Develpoed area for instance more commercial or residential area is more likely to attract more visits by taxis, as well as dense public facilities but with more temporal variations.
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Knowing the characteristics of intra-city movement is very important in understanding complex space-time dynamics during urban study. The interactions between intra-city movement and land use have been discussing for many years. Waddell (2002) introduced a new model system, UrbanSim, to link planning of land use, transportation, and environmental quality. Han et al. (2011) explored human traveling patterns and found human traveling behaviors were strongly affected by the geographical structure. Thus, understanding the relationships between intra-city movement and land use can help us to develop sustainable urban planning that avoids excessive intra-city movements, reduces traffic congestions, and makes the city more livable. Meanwhile, given urban landscape, researchers can measure intra-city movement in advance and develop appropriate transportation system. Furthermore, the characteristics of intra-city movement are necessary in developing efficient methods in transportation simulation, demand forecasting and traffic control. Kitamura et al. (2000) developed a micro-simulator for trip generation, according to daily activity-travel patterns. Thus, researchers can predict trip generations, attractions, and routes, and then measure traffic conditions dynamically on urban road network. Related authorities can implement some special and efficient countermeasures in advance to cope with potential congestion or other traffic incidents.

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