Contact us
[email protected] | |
3275638434 | |
Paper Publishing WeChat |
Useful Links
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Article
Driving Behavior Assessment Using Fuzzy Inference System and Low-Cost Inertial Sensors
Author(s)
Neda Navidi and Rene Jr. Landry
Full-Text PDF XML 800 Views
DOI:10.17265/2328-2142/2017.04.003
Affiliation(s)
LASSENA, Department of Electrical Engineering, École de Technologie Supérieure (ETS), Montreal, QC H3C 1K3, Canada
ABSTRACT
Continuous vehicle tracking as well as monitoring driving behaviour, is significant services
that are needed by many industries including insurance and vehicle rental
companies. The main goal of this paper is to provide methods to model the
quality of the driving behaviour based on FIS (fuzzy inference systems). The models consider vehicle dynamics as long
as the human behaviour parameters, expressed by a set of raw measurements which
are obtained from various environmental sensors. In addition,
assessment-driving behaviour model is simulated and tested by two different
FISs: Mamdani and Sugeno-TSK. The simulation results illustrate the critical
distinctions between the two FISs using the proposed driving behaviour models.
These differences are based on various processing times, robust behaviour of
the FISs, outputs MFs (membership functions), fuzzification-techniques, flexibility in the systems design and
computational efficiency.
KEYWORDS
Driving behaviour assessment, FIS, Mamdani type, Sugeno-TSK type, MFs.
Cite this paper
References