During the latest years, Powered Two Wheelers (PTW) have become a complete game-changer in everyday commuting, since their distinctive characteristics from the rest of the traffic make them an attractive means of transport. However, PTW related studies are mostly safety oriented probably due to the lack of naturalistic driving data. Although there have been studies that extract PTW trajectories from video recordings, limitations such as the arterial monitoring extent, and conspicuity issues, can affect the quality of results and research opportunities. In this paper, the above-mentioned limitations are reviewed and novel data collection capabilities and directions are identified using Unmanned Aerial Systems (UAS). The advantages of UAS monitoring traffic streams from above as an “eye-in-the-sky” solution, covering large areas in short time intervals and discreetly recording drivers’ behavior can play an important role when it comes to creating naturalistic datasets. The discussion concludes by underlining that, if technical, privacy and legal issues that have emerged from their early use are to be tackled, UAS can be transformed into an integral part of the Intelligent Transportation System (ITS) infrastructure.
| ID | pc261 |
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| Tags | big data, driver behaviour, machine learning, motorcyclists, naturalistic driving, telematics |
