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Understanding the characteristics of passenger vehicle use is the prerequisite for effective urban management. However, it has been challenging in the existing literature due to the lack of continuously observed data on passenger vehicle use. Thanks to the advances in data collection and processing techniques, multi-day vehicle trajectory data generated from volunteered passenger cars provide new opportunities for examining in depth how people travel in regular patterns. In this paper, based on a week's operation data of 6600 passenger cars in Shanghai, we develop a systematic approach for identifying trips and travel purposes, and classify vehicles into four categories using a Gaussian-Mixed-Model. A new method is proposed to identify vehicle travel regularities and we use the Z Test to explore differences in travel time and route choices between four types of vehicles. We find that commercially used vehicles present high travel intensity in temporal and spatial aspects and the use intensity in elevated roads is higher for household-used commuting vehicles than semi-commercially used vehicles. The methodologies and conclusions of this paper may provide not only theoretical support for future urban traffic prediction, but also guidance for employing customized active traffic demand management measures to alleviate traffic congestion. [ABSTRACT FROM AUTHOR]

The concept of "consumer city" has reshaped the growth and prosperity of major cities in the world. Although the literature has extensively documented the role of central cities in generating jobs, there has been limited empirical evidence on how those cities have developed into agglomerations of consumption opportunities by offering metropolitan residents high-quality consumer goods and services. We use large-scale cellular signaling data to distinguish commuting and consumption connections between the Shanghai City and a suburban town Huaqiao. Through the clustering algorithm, we categorize residents of Huaqiao into groups according to their frequency of visiting Shanghai and length of the visits. Results show that while travel time does not differ across the three groups of trips, non-commuters' consumption trips are more spatially expansive and intensive than the others. The average per capita visit frequencies also indicate the outstanding role of consumption-oriented travel. Spatial lag models suggest that although non-commuters are more sensitive to travel time than commuters, they are still willing to make long consumption trips to access the consumer goods and services the central city can provide. The findings would encourage city managers and planners to reconsider the roles of major cities, and redefine them as space that best match the changing demand of people. • Concept of "consumer city" is tested with cellular signaling data in Shanghai. • Commuting and consumption travel of residents in a suburban town are studied. • Core city accommodates demand for accessing various socioeconomic opportunities. • Non-commuters' consumption trips are more expansive and intensive than commuting trips. • Non-commuters are willing to make long consumption trips to the core city. [ABSTRACT FROM AUTHOR]