A Decision Support Model for Transportation Companies to Examine Driver Behavior
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F21%3A39918136" target="_blank" >RIV/00216275:25510/21:39918136 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9524537" target="_blank" >https://ieeexplore.ieee.org/document/9524537</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TEM.2021.3102879" target="_blank" >10.1109/TEM.2021.3102879</a>
Alternative languages
Result language
angličtina
Original language name
A Decision Support Model for Transportation Companies to Examine Driver Behavior
Original language description
The entire society, and particularly the transportation companies, has an interest to improve traffic safety. Besides more than 3000 lost lives on the roads every day, there are significant financial consequences of road traffic accidents (RTAs). The purpose of this article is to design an efficient model for providing information about driver propensity for RTAs based on assessing their personality traits. This is achieved by creating a fuzzy inference system (FIS) where inputs are the scores from the implemented psychological instruments and output is the number of RTAs experienced by a driver. To adjust the functioning of FIS to the empirical data, a bee colony optimization (BCO) metaheuristic is applied. In this optimization procedure, we test three approaches for defining the variables of initial FIS and compare their performance. Simulation results show the differences between the considered approaches and, generally, very promising achievements of the proposed algorithm. The best-found FIS reached a 36% improvement of the objective function compared to the starting FIS. This FIS can be used, inter alia, as a decision-making tool in recruitment procedures for professional drivers to assess their propensity for RTAs, by that saving the lives of people and reducing the costs of the companies.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50203 - Industrial relations
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Engineering Management
ISSN
0018-9391
e-ISSN
—
Volume of the periodical
Neuveden
Issue of the periodical within the volume
AUG 2021
Country of publishing house
US - UNITED STATES
Number of pages
13
Pages from-to
1-13
UT code for WoS article
000732624100001
EID of the result in the Scopus database
—