Evaluation of professional driver’s eco-driving skills based on type-2 fuzzy logic model

Due to the great market competition, transport companies face the need to reduce their vehicle fleet costs. The vehicle fleet managers’ actions on the driver’s driving style to achieve fuel consumption savings are measures to increase the fleet’s energy efficiency. The authors developed a model for...

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Bibliographic Details
Published in:Neural computing & applications 2021-09, Vol.33 (18), p.11541-11554
Main Authors: Zdravković, Stefan, Vujanović, Davor, Stokić, Marko, Pamučar, Dragan
Format: Article
Language:English
Subjects:
Acceleration
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Deceleration
Energy efficiency
Evaluation
Fuel consumption
Fuzzy logic
Image Processing and Computer Vision
Mathematical models
Model testing
Original Article
Parameters
Probability and Statistics in Computer Science
Training
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Summary:Due to the great market competition, transport companies face the need to reduce their vehicle fleet costs. The vehicle fleet managers’ actions on the driver’s driving style to achieve fuel consumption savings are measures to increase the fleet’s energy efficiency. The authors developed a model for evaluating driving style using a type-2 fuzzy logic system. The model comprehensively considers three parameters: engine speed, accelerator pedal position, and acceleration/deceleration. These parameters can precisely describe the driving style and additionally have a strong influence on fuel consumption. The model output is the driver’s score, representing the influence of driving style to fuel consumption. The model is tested in the company whose drivers have attended the eco-driving training course. Each driver’s driving style was monitored for 15 days to obtain trustworthy assessments regarding driving style. The result was twofold: firstly, we point out the importance of simultaneous observation of all three defined parameters to get reliable driver’s score in terms of driving style, and secondly, it is established that drivers have significantly different driving styles regardless of whether they have attended the same eco-driving training. The established differences in driving styles have a direct impact on the obtained differences in fuel consumption among drivers. The proposed model can significantly reduce fuel consumption depending on the driving style and increase the vehicle fleet’s energy efficiency.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-021-05823-z