Extracting Insights from Large-Scale Telematics Data for ITS Applications: Lessons and Recommendations
Gibran Ali, Neal Feierabend, Prarthana Doshi, Calvin Winkowski, Michael Fontaine

TL;DR
This paper develops a data processing pipeline and visualization tools for large-scale telematics data, providing insights into trip behavior and roadway speeds to aid transportation planning and vehicle manufacturers.
Contribution
It introduces a scalable data analysis framework, an open data repository, and visualization tools for telematics data, addressing standardization and processing challenges.
Findings
Analyzed 1.4 billion miles of telematics data.
Created an open repository of trip and roadway summaries.
Identified key challenges and provided recommendations for data processing.
Abstract
Over 90% of new vehicles in the United States now collect and transmit telematics data. Similar trends are seen in other developed countries. Transportation planners have previously utilized telematics data in various forms, but its current scale offers significant new opportunities in traffic measurement, classification, planning, and control. Despite these opportunities, the enormous volume of data and lack of standardization across manufacturers necessitates a clearer understanding of the data and improved data processing methods for extracting actionable insights. This paper takes a step towards addressing these needs through four primary objectives. First, a data processing pipeline was built to efficiently analyze 1.4 billion miles (120 million trips) of telematics data collected in Virginia between August 2021 and August 2022. Second, an open data repository of trip and roadway…
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Taxonomy
TopicsTraffic Prediction and Management Techniques · Traffic control and management · Human Mobility and Location-Based Analysis
