101. Processing and Analyzing Real-World Driving Data: Insights on Trips, Scenarios, and Human Driving Behaviors
- Author
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Han, Jihun, Karbowski, Dominik, Moawad, Ayman, Kim, Namdoo, Rousseau, Aymeric, Fan, Shihong, Lee, Jason Hoon, and Ha, Jinho
- Subjects
Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Human-Computer Interaction - Abstract
Analyzing large volumes of real-world driving data is essential for providing meaningful and reliable insights into real-world trips, scenarios, and human driving behaviors. To this end, we developed a multi-level data processing approach that adds new information, segments data, and extracts desired parameters. Leveraging a confidential but extensive dataset (over 1 million km), this approach leads to three levels of in-depth analysis: trip, scenario, and driving. The trip-level analysis explains representative properties observed in real-world trips, while the scenario-level analysis focuses on scenario conditions resulting from road events that reduce vehicle speed. The driving-level analysis identifies the cause of driving regimes for specific situations and characterizes typical human driving behaviors. Such analyses can support the design of both trip- and scenario-based tests, the modeling of human drivers, and the establishment of guidelines for connected and automated vehicles.
- Published
- 2025