The main topic of this dissertation is the modeling of driver behavior based on an
examination of their psychological traits. After a detailed review of relevant literature,
five questionnaires have been prepared to collect the data. Four questionnaires are
related to testing the psychological constructs of drivers and an additional one is a
demographical and driving history questionnaire. A survey was carried out at the sample
of 305 drivers, from which there were 202 professional drivers and 103 drivers of
privately owned vehicles. The data were processed by two general approaches: statistical
and fuzzy logic. The implemented statistical methods are hierarchical regression analysis
and binary logistic regression. The driver behavior is modeled by fuzzy inference systems
where the inputs are the results from psychological tests and the output is the number of
experienced road traffic accidents in driving history. The performance of a fuzzy inference
system that can be considered as a decision?]making tool for explaining driver behavior, is
further enhanced, in the sense of adjusting its results to the empirical data, by applying
the bee colony optimization metaheuristic. Based on the obtained results, adequate
recommendations for traffic safety improvement are proposed.
Anotace v angličtině
The main topic of this dissertation is the modeling of driver behavior based on an
examination of their psychological traits. After a detailed review of relevant literature,
five questionnaires have been prepared to collect the data. Four questionnaires are
related to testing the psychological constructs of drivers and an additional one is a
demographical and driving history questionnaire. A survey was carried out at the sample
of 305 drivers, from which there were 202 professional drivers and 103 drivers of
privately owned vehicles. The data were processed by two general approaches: statistical
and fuzzy logic. The implemented statistical methods are hierarchical regression analysis
and binary logistic regression. The driver behavior is modeled by fuzzy inference systems
where the inputs are the results from psychological tests and the output is the number of
experienced road traffic accidents in driving history. The performance of a fuzzy inference
system that can be considered as a decision?]making tool for explaining driver behavior, is
further enhanced, in the sense of adjusting its results to the empirical data, by applying
the bee colony optimization metaheuristic. Based on the obtained results, adequate
recommendations for traffic safety improvement are proposed.
The main topic of this dissertation is the modeling of driver behavior based on an
examination of their psychological traits. After a detailed review of relevant literature,
five questionnaires have been prepared to collect the data. Four questionnaires are
related to testing the psychological constructs of drivers and an additional one is a
demographical and driving history questionnaire. A survey was carried out at the sample
of 305 drivers, from which there were 202 professional drivers and 103 drivers of
privately owned vehicles. The data were processed by two general approaches: statistical
and fuzzy logic. The implemented statistical methods are hierarchical regression analysis
and binary logistic regression. The driver behavior is modeled by fuzzy inference systems
where the inputs are the results from psychological tests and the output is the number of
experienced road traffic accidents in driving history. The performance of a fuzzy inference
system that can be considered as a decision?]making tool for explaining driver behavior, is
further enhanced, in the sense of adjusting its results to the empirical data, by applying
the bee colony optimization metaheuristic. Based on the obtained results, adequate
recommendations for traffic safety improvement are proposed.
Anotace v angličtině
The main topic of this dissertation is the modeling of driver behavior based on an
examination of their psychological traits. After a detailed review of relevant literature,
five questionnaires have been prepared to collect the data. Four questionnaires are
related to testing the psychological constructs of drivers and an additional one is a
demographical and driving history questionnaire. A survey was carried out at the sample
of 305 drivers, from which there were 202 professional drivers and 103 drivers of
privately owned vehicles. The data were processed by two general approaches: statistical
and fuzzy logic. The implemented statistical methods are hierarchical regression analysis
and binary logistic regression. The driver behavior is modeled by fuzzy inference systems
where the inputs are the results from psychological tests and the output is the number of
experienced road traffic accidents in driving history. The performance of a fuzzy inference
system that can be considered as a decision?]making tool for explaining driver behavior, is
further enhanced, in the sense of adjusting its results to the empirical data, by applying
the bee colony optimization metaheuristic. Based on the obtained results, adequate
recommendations for traffic safety improvement are proposed.
Po představení doktorandky byla komise seznámena se stanoviskem školitele a vedoucím školícího pracoviště k disertační práci. Doktorandka seznámil komisi se svojí disertační prací formou prezentace. Poté byly předneseny posudky oponentů a doktorandka uspokojivě reagovala na připomínky oponentů. V následné veřejné diskusi byly zodpovězeny otázky členů komise, které jsou uvedeny na samostatných listech. Na závěr proběhlo tajné hlasování. Protokol o výsledcích hlasování tvoří samostatnou přílohu.