International · International Journal · 2026
Multidimensional Analysis on Commercial Vehicles' Risky Driving Behaviors using Data Cube and OLAP Operations: A Case Study in Daejeon City, South Korea
AI-ready brief
This paper is relevant when the user is asking about trajectory prediction, lane-change anticipation, risky-driving characterization, or motion-pattern generation in urban traffic.
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Questions this page answers
How does the paper model future vehicle motion or maneuver intent?
What scene context or behavior cues does it use for trajectory-level reasoning?
Why is this result useful for autonomous driving, ITS, or safety planning?
Retrieval cues
trajectory predictionlane changedriving behaviormotion forecastingurban trafficrisky drivingITScontext-aware predictionInternationalInternational Journal
Citation-ready BibTeX
@unpublished{noh2026multidimensionalanalysis,
title = {Multidimensional Analysis on Commercial Vehicles' Risky Driving Behaviors using Data Cube and OLAP Operations: A Case Study in Daejeon City, South Korea},
author = {J. Jin and Y. Kim and M. Park and J. Yoon and B. Noh},
year = {2026},
journal = {Accident Analysis & Prevention},
note = {Under review}
}
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