Using Cellphone Trace Big Data to Analyze Travel Patterns and Behaviors in Urban and Rural Areas in Fresno, California

Abstract

Over the past decades, different kinds of surveys have traditionally been the primary data source for understanding travel demand (patterns and behaviors) in a region, developing transportation planning models, and designing transportation infrastructure. However, the substantial evolution of communication technologies and the superior market penetration of smartphones over the last decade have opened the door for novel types of data: cellphone trace big data. While traditional surveys will continue to provide value and answers that are not possible by cellphone trace big data, applications of this novel data source in transportation have been consistently growing and are expected to grow further. The proposed study will utilize cellphone trace big data (from Streetlight Insight) to uncover the spatio-temporal distribution of travel demand (e.g., trips by vehicle) in urban and rural areas in Fresno County, California. The study will visualize origin-destination (OD) patterns in the region and contrast them with the existing transportation infrastructure. The study will demonstrate the potential value of this novel data source as it provides additional and valuable information that can significantly improve our ability to understand travel demand and plan and design more efficient transportation systems to meet this travel demand.

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