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http://dx.doi.org/10.12815/kits.2020.19.5.70

Probe Vehicle Data Collecting Intervals for Completeness of Link-based Space Mean Speed Estimation  

Oh, Chang-hwan (Dept. of Urban Eng., Chungbuk National University)
Won, Minsu (Division for Research of AI and Big Data, The Korea Transport Institute)
Song, Tai-jin (Dept. of Urban Eng., Chungbuk National University)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.19, no.5, 2020 , pp. 70-81 More about this Journal
Abstract
Point-by-point data, which is abundantly collected by vehicles with embedded GPS (Global Positioning System), generate useful information. These data facilitate decisions by transportation jurisdictions, and private vendors can monitor and investigate micro-scale driver behavior, traffic flow, and roadway movements. The information is applied to develop app-based route guidance and business models. Of these, speed data play a vital role in developing key parameters and applying agent-based information and services. Nevertheless, link speed values require different levels of physical storage and fidelity, depending on both collecting and reporting intervals. Given these circumstances, this study aimed to establish an appropriate collection interval to efficiently utilize Space Mean Speed information by vehicles with embedded GPS. We conducted a comparison of Probe-vehicle data and Image-based vehicle data to understand PE(Percentage Error). According to the study results, the PE of the Probe-vehicle data showed a 95% confidence level within an 8-second interval, which was chosen as the appropriate collection interval for Probe-vehicle data. It is our hope that the developed guidelines facilitate C-ITS, and autonomous driving service providers will use more reliable Space Mean Speed data to develop better related C-ITS and autonomous driving services.
Keywords
Big Data; Probe-vehicle Data; Space Mean Speed; Local Dynamic Map;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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