Influential Factors on Braking Coefficients and Variability in Braking Force of Vehicle Service Brakes: A Neural Network Approach

Vehicles comprise several critical systems, including the braking, steering, transmission, and suspension systems, which operate in concert to ensure safe and efficient movement.Research has established that vehicle malfunctions, particularly in the braking system, contribute significantly to road accidents, with technical failures accounting for approximately 15% of crashes and brake system failures responsible for 17.4% of these incidents.In light of this, an investigation was conducted to identify the factors that influence the braking coefficient and the variability of braking force in vehicle service brakes.A total of 1,018 vehicles were involved in the study, with results indicating that variables such as vehicle production year, category, place of registration, engine power and displacement, gross and curb weight, and payload significantly affect the braking coefficient.Furthermore, the analysis revealed that factors such as vehicle production year, category, registration location, gross and curb weight, and payload are prominent in determining the braking force variability.Neural network analysis was employed to further assess these influential factors, highlighting that the year of manufacture, place of registration, and vehicle payload are particularly influential in predicting both compliance with minimum braking coefficient requirements and variations in braking force.The findings underscore the importance of these factors in the development of more precise models for vehicle brake performance, with potential implications for safety standards and regulatory frameworks.

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Publication Details

Journal
Mechatronics and intelligent transportation systems
Published
2025-10-13
DOI
https://doi.org/10.56578/mits040401
Primary Topic
Brake Systems and Friction Analysis
Type
article
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article

Influential Factors on Braking Coefficients and Variability in Braking Force of Vehicle Service Brakes: A Neural Network Approach

Saša Vasiljević, Sreten Simović, Aleksandar Trifunović, Tijana Ivanišević
Mechatronics and intelligent transportation systems
Brake Systems and Friction Analysis
article

Influential Factors on Braking Coefficients and Variability in Braking Force of Vehicle Service Brakes: A Neural Network Approach

Saša Vasiljević, Sreten Simović, Aleksandar Trifunović, Tijana Ivanišević
article en

Abstract

Vehicles comprise several critical systems, including the braking, steering, transmission, and suspension systems, which operate in concert to ensure safe and efficient movement.Research has established that vehicle malfunctions, particularly in the braking system, contribute significantly to road accidents, with technical failures accounting for approximately 15% of crashes and brake system failures responsible for 17.4% of these incidents.In light of this, an investigation was conducted to identify the factors that influence the braking coefficient and the variability of braking force in vehicle service brakes.A total of 1,018 vehicles were involved in the study, with results indicating that variables such as vehicle production year, category, place of registration, engine power and displacement, gross and curb weight, and payload significantly affect the braking coefficient.Furthermore, the analysis revealed that factors such as vehicle production year, category, registration location, gross and curb weight, and payload are prominent in determining the braking force variability.Neural network analysis was employed to further assess these influential factors, highlighting that the year of manufacture, place of registration, and vehicle payload are particularly influential in predicting both compliance with minimum braking coefficient requirements and variations in braking force.The findings underscore the importance of these factors in the development of more precise models for vehicle brake performance, with potential implications for safety standards and regulatory frameworks.

Mechatronics and intelligent transportation systemsVol. 4(4)
Openalex Percentile: Top 69%
Brake Systems and Friction Analysis
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Influential Factors on Braking Coefficients and Variability in Braking Force of Vehicle Service Brakes: A Neural Network Approach — Saša Vasiljević, Sreten Simović, et al. · Mechatronics and intelligent transportation systems (2025) | TGRS Research Map | TGRS