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Article type: Research Article
Authors: Suresh, M.a; * | Venkata Satya Vivek, Tammineedib | Venkat, Yallac | Chokkalingam, Mohand
Affiliations: [a] Department of CSE, DMI College of Engineering, Chennai, India | [b] Associate Professor, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India | [c] Professor in Computer Science Engineering, BVC College of Engineering, Palacharla, Rajanagaram Mandal, East Godavari District, A.P, India | [d] Department of Nanoelectronics Materials and Sensor, Institute of Electronic and Communication Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Science, Chennai
Correspondence: [*] Corresponding author. M. Suresh, Professor, Department of CSE, DMI College of Engineering, Chennai, India. E-mail: dr.mariasuresh@gmail.com.
Abstract: The lack of awareness of blind spots in vehicle transport results in more deaths nowadays. To address this issue, the multi-obstacle detection and measurement of the depth of the nearing vehicle, height, and width is necessary. In recent years, Fuzzy logic is being used to access smart decision-making for control actions. To handle the specific task efficiently, ambiguous and imprecise linguistic data is required. In this context, a non-linear intelligent fuzzy decision-making system has been proposed to estimate blind spots. An inference engine, a defuzzification interface to identify the blind spot both day and night, and a fuzzy rule-base are included. Shadows and edges can be used as linguistic parameters to identify vehicles in the daytime. The lamps are elevated higher than the air dams to avoid casting a shadow under the car at night. One in-sourcing vehicle and three out-sourcing vehicles are tested to determine the driver’s blind spot and a more comfortable driver’s seat and a rear-view mirror using the proposed system. A fuzzy matrix with a triangular number obtained from the crisp matrix is used to alert the driver of the likelihood of a collision using LEDs or buzzers.
Keywords: Non-linearity, Fuzzy decision-making system, blind spot estimation, vehicle detection system
DOI: 10.3233/JIFS-213426
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 1, pp. 139-148, 2023
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