Ghasemi, Navid
(2020)
Improvement of The Driver Simulator Control and Comparison Between Driver-Road-Vehicle Interaction in Real and Simulated Environment, [Dissertation thesis], Alma Mater Studiorum Università di Bologna.
Dottorato di ricerca in
Ingegneria civile, chimica, ambientale e dei materiali, 32 Ciclo. DOI 10.48676/unibo/amsdottorato/9187.
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Abstract
The present doctoral thesis discusses the ways to improve the performance of driving simulator, provide objective measures for the road safety evaluation methodology based on driver’s behavior and response and investigates the drivers' adaptation to the driving assistant systems.
The activities are divided into two macro areas; the driving simulation studies and on-road experiments.
During the driving simulation experimentation, the classical motion cueing algorithm with logarithmic scale was implemented in the 2DOF motion cueing simulator and the motion cues were found desirable by the participants. In addition, it found out that motion stimuli could change the behaviour of the drivers in terms of depth/distance perception.
During the on-road experimentations, The driver gaze behaviour was investigated to find the objective measures on the visibility of the road signs and reaction time of the drivers. The sensor infusion and the vehicle monitoring instruments were found useful for an objective assessment of the pavement condition and the drivers’ performance.
In the last chapter of the thesis, the safety assessment during the use of level 1 automated driving “ACC” is discussed with the simulator and on-road experiment. The drivers’ visual behaviour was investigated in both studies with innovative classification method to find the epochs of the distraction of the drivers. The behavioural adaptation to ACC showed that drivers may divert their attention away from the driving task to engage in secondary, non-driving-related tasks.
Abstract
The present doctoral thesis discusses the ways to improve the performance of driving simulator, provide objective measures for the road safety evaluation methodology based on driver’s behavior and response and investigates the drivers' adaptation to the driving assistant systems.
The activities are divided into two macro areas; the driving simulation studies and on-road experiments.
During the driving simulation experimentation, the classical motion cueing algorithm with logarithmic scale was implemented in the 2DOF motion cueing simulator and the motion cues were found desirable by the participants. In addition, it found out that motion stimuli could change the behaviour of the drivers in terms of depth/distance perception.
During the on-road experimentations, The driver gaze behaviour was investigated to find the objective measures on the visibility of the road signs and reaction time of the drivers. The sensor infusion and the vehicle monitoring instruments were found useful for an objective assessment of the pavement condition and the drivers’ performance.
In the last chapter of the thesis, the safety assessment during the use of level 1 automated driving “ACC” is discussed with the simulator and on-road experiment. The drivers’ visual behaviour was investigated in both studies with innovative classification method to find the epochs of the distraction of the drivers. The behavioural adaptation to ACC showed that drivers may divert their attention away from the driving task to engage in secondary, non-driving-related tasks.
Tipologia del documento
Tesi di dottorato
Autore
Ghasemi, Navid
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Real-time vehicle simulation
Motion cueing algorithm
Surrogate safety measures
Eye-tracking
Driver Reaction Time
URN:NBN
DOI
10.48676/unibo/amsdottorato/9187
Data di discussione
28 Aprile 2020
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Ghasemi, Navid
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Real-time vehicle simulation
Motion cueing algorithm
Surrogate safety measures
Eye-tracking
Driver Reaction Time
URN:NBN
DOI
10.48676/unibo/amsdottorato/9187
Data di discussione
28 Aprile 2020
URI
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