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Title of the article

CLASSIFICATION OF RELEVANT INFORMATION FOR DRIVERS IN HIGHLY AUTOMATED VEHICLES
Authors

SAVCHENKO Vladimir V., Ph. D. in Eng., Chief of the R&D Center “Onboard control systems of mobile machines”, Joint Institute of Mechanical Engineering of the NAS of Belarus, Minsk, Republic of Belarus, This email address is being protected from spambots. You need JavaScript enabled to view it.">This email address is being protected from spambots. You need JavaScript enabled to view it.

LITAROVICH Veranika V., Junior Researcher, Joint Institute of Mechanical Engineering of the NAS of Belarus, Minsk, Republic of Belarus, This email address is being protected from spambots. You need JavaScript enabled to view it.">This email address is being protected from spambots. You need JavaScript enabled to view it.
In the section MECHANICS OF MOBILE MACHINES
Year 2020 Issue 3 Pages 27–33
Type of article RAR Index UDK 629.3.06+656.13+612.821 Index BBK  
DOI https://doi.org/10.46864/1995-0470-2020-3-52-27-33
Abstract The search for ways to solve the problem of transferring control to the driver in highly automated vehicles involves the development of new methods and adaptation of the known ones for this purpose. The development of the method of monitoring the perception of semantically binary relevant information by the driver implies the identification of sources of significant information and classification of relevant information for drivers coming from ADAS, ITS and the dashboard. Determination of the driver’s temporal response to the incoming relevant information and its subsequent analysis will allow in real time, during the execution of the algorithms of the activity on the management of the highly automated vehicle, without using the additional equipment, to monitor and update the particular driver’s database containing quantitative values that characterize a number of its professionally important qualities, in automatic mode, with the use of cloud servers. The obtained results are focused on the solution of the problem of control transfer to the driver in highly automated vehicles, when the vehicle’s onboard systems cannot support further “unmanned” mode of control and the vehicle is not within a specific operational design domain.
Keywords

ADAS, highly automated vehicles, operational design domain, individual features of the driver, transfer of control to the driver, professionally important qualities, semantically binary relevant information, traffic situation along the route
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