As the demand for active transportation infrastructure increases, strategies must be developed by planners and policymakers to determine where to connect an active transportation network that supports physical activity in an equitable, safe, and inclusive way. In place of the traditional household travel survey, this case study explores the use of a mobile phone Big Data data set focused on travel behavior applications called Replica and how it can be applied to understand the characteristics of trips within a given geography. Fresno, California, is characterized by its variety of land uses, from rural to suburban and even dense urban areas, serving as an ideal case study location, sharing traits of many cities across the United States. This paper presents a methodology that begins with the validation of Replica data. Quantitative and qualitative analyses of Replica trip data by travel mode then revealed several key findings: (1) the main trip purposes of biking trips in Fresno are Home and School, (2) the majority of biking trip takers are under 18, and (3) travel mode may be indicative of income level. The outcomes of this case study would serve those advocating for the implementation of active transportation infrastructure or who are involved in the development of an active transportation plan.


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    Title :

    Mobility Behavior and Patterns Using Cell Phone Trace Data: A Case Study of Fresno, California


    Contributors:

    Conference:

    International Conference on Transportation and Development 2025 ; 2025 ; Glendale, Arizona



    Publication date :

    2025-06-05




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English