Work

Uncertainty in Cell-Phone Generated Bike and Pedestrian Volumes

Year: 2025

Type: article

Abstract: Big data from mobile phones are increasingly used in transport research and planning, offering unprecedented spatial and temporal detail. However, data accuracy remains unclear. This study evaluates Replica, a dataset modelled from mobile phone GPS data, by comparing modeled volumes for motor vehicles, bicycles, and pedestrians against field counts in Santa Barbara, California. Car volumes were modeled with high accuracy (R² = 0.92), while bicycle (R² = 0.23) and pedestrian (R² = 0.05) estimates showed substantial uncertainty. When using transport data generated from mobile phone GPS, additional caution is needed for non-motorized modes.

Source: Findings

DOI: 10.32866/001c.145234

Authors: Lily Heidger, Trisalyn Nelson, Dan Willett

Institution: University of California, Santa Barbara

Language: English

Topic: Human Mobility and Location-Based Analysis

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $100