Need data for driver behaviour analysis? Presenting the public UAH-DriveSet

2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)(2016)

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摘要
Driving analysis is a recent topic of interest due to the growing safety concerns in vehicles. However, the lack of publicly available driving data currently limits the progress on this field. Machine learning techniques could highly enhance research, but they rely on large amounts of data which are difficult and very costly to obtain through Naturalistic Driving Studies (NDSs), resulting in limited accessibility to the general research community. Additionally, the proliferation of smartphones has provided a cheap and easy-to-deploy platform for driver behavior sensing, but existing applications do not provide open access to their data. For these reasons, this paper presents the UAH-DriveSet, a public dataset that allows deep driving analysis by providing a large amount of data captured by our driving monitoring app DriveSafe. The application is run by 6 different drivers and vehicles, performing 3 different behaviors (normal, drowsy and aggressive) on two types of roads (motorway and secondary road), resulting in more than 500 minutes of naturalistic driving with its associated raw data and processed semantic information, together with the video recordings of the trips. This work also introduces a tool that helps to plot the data and display the trip videos simultaneously, in order to ease data analytics. The UAH-DriveSet is available at: http:// www.robesafe.com/personal/eduardo.romera/uah-driveset.
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关键词
driver behaviour analysis,public UAH-DriveSet,machine learning techniques,naturalistic driving studies,NDSs,smartphones,driver behavior sensing,driving monitoring app DriveSafe,semantic information,video recordings,data analytics
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