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      Performance validation of vehicle platooning through intelligible analytics

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          Abstract

          The study deals with intelligible analytics for performance modelling of vehicle platooning. Knowledge extraction with rules is targeted to understand safety regions (collision avoidance) of system parameters. Results are shown by feeding data through simulation to the train of different rule extraction mechanisms. Safety regions are evidenced on test data with statistical error very close to zero.

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          Most cited references 19

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          A tutorial on support vector machines for pattern recognition

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            A Survey on Platoon-Based Vehicular Cyber-Physical Systems

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              Platooning With IVC-Enabled Autonomous Vehicles: Strategies to Mitigate Communication Delays, Improve Safety and Traffic Flow

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                Author and article information

                Contributors
                Journal
                IET-CPS
                IET Cyber-Physical Systems: Theory & Applications
                IET Cyber-Phys. Syst., Theory Appl.
                The Institution of Engineering and Technology
                2398-3396
                2398-3396
                19 October 2018
                8 January 2019
                June 2019
                : 4
                : 2
                : 120-127
                Affiliations
                [1 ] Institute of Electronics, Computer and Telecommunication Engineering, National Research Council of Italy , Genova, Italy
                [2 ] Impara S.r.l ., Genova, Italy
                Article
                IET-CPS.2018.5055 CPS.2018.5055
                10.1049/iet-cps.2018.5055

                This is an open access article published by the IET under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                Page count
                Pages: 0
                Product
                Funding
                Funded by: Horizon 2020 Framework Programme
                Award ID: 692529-2
                Categories
                Research Article

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