Driver evaluation in heavy duty vehicles based on acceleration and braking behaviors

Mumcuoğlu, Mehmet Emin and Alcan, Gökhan and Ünel, Mustafa and Çiçek, Onur and Mutluergil, Mehmet and Yılmaz, Metin and Köprübaşı, Kerem (2020) Driver evaluation in heavy duty vehicles based on acceleration and braking behaviors. In: 46th Annual Conference of the IEEE Industrial Electronics Society (IECON 2020), Singapore

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In this paper, we present a real-time driver evalua-tion system for heavy-duty vehicles by focusing on the classifica-tion of risky acceleration and braking behaviors. We utilize animproved version of our previous Long Short Memory (LSTM)based acceleration behavior model [10] to evaluate varyingacceleration behaviors of a truck driver in small time periods.This model continuously classifies a driver as one of six driverclasses with specified longitudinal-lateral aggression levels, usingdriving signals as time-series inputs. The driver gets accelerationscore updates based on assigned classes and the geometry ofdriven road sections. To evaluate the braking behaviors of atruck driver, we propose a braking behavior model, which usesa novel approach to analyze deceleration patterns formed duringbrake operations. The braking score of a driver is updated foreach brake event based on the pattern, magnitude, and frequencyevaluations. The proposed driver evaluation system has achievedsignificant results in both the classification and evaluation ofacceleration and braking behaviors.
Item Type: Papers in Conference Proceedings
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics
Sabancı University Nanotechnology Research and Application Center
Faculty of Engineering and Natural Sciences
Depositing User: Mustafa Ünel
Date Deposited: 24 Sep 2020 14:01
Last Modified: 26 Apr 2022 09:37

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