TripMD: Driving patterns investigation via Motif Analysis

• URL: http://arxiv.org/abs/2007.03727v4
• Date: Mon, 5 Jul 2021 16:49:18 GMT
• Title: TripMD: Driving patterns investigation via Motif Analysis
• Authors: Maria In\^es Silva, Roberto Henriques
• Abstract summary: TripMD is a system that extracts the most relevant driving patterns from sensor recordings. We show that our system can extract a rich number of driving patterns from a single driver.
• Score: 3.42658286826597
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Processing driving data and investigating driving behavior has been receiving an increasing interest in the last decades, with applications ranging from car insurance pricing to policy making. A common strategy to analyze driving behavior is to study the maneuvers being performance by the driver. In this paper, we propose TripMD, a system that extracts the most relevant driving patterns from sensor recordings (such as acceleration) and provides a visualization that allows for an easy investigation. Additionally, we test our system using the UAH-DriveSet dataset, a publicly available naturalistic driving dataset. We show that (1) our system can extract a rich number of driving patterns from a single driver that are meaningful to understand driving behaviors and (2) our system can be used to identify the driving behavior of an unknown driver from a set of drivers whose behavior we know.

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