ABSTRACT
The safety of passengers is an important aspect of developing a car with superlative automaticity. Human error accounts for 94% of serious crashes, according to the National Highway Traffic Safety Administration (NHTSA). Autonomous vehicles or self-driving cars may respond more quickly than human drivers, theoretically (Shwartz, 2021). The purpose of this study was to analyze those human errors or potential factors that affected the decision-making ability of a human driver that led to errors. A simulation was built to represent a real-life driving experience to accomplish this goal. Participant-drivers drive in a simulated city with busy traffic, 3-way to 5-way intersections, and complex routes. Pedestrians, flashing and non-flashing road signs and distractions are also prevalent in the city. Data from an eye tracker device was collected in the form of fixation maps and heat maps to determine the driver's visual focus areas. Previous studies have shown that drivers tend to focus mainly on the road straight ahead (Mauk, 2020). Hence, few changes have been made in this study to collect more precise data. The results have shown that the drivers are more attentive in busy/occupying scenarios. Along with that, the study indicated that 70% of the drivers followed the actions of vehicles that were in front of them. This study also explored the dissimilarity of driving patterns of the same driver on a non-familiarized road versus a familiarized road. From the dissimilarities, it was established that the drivers were at ease while driving in the simulation for the second time in comparison to the first time. However, the drivers' visual span seemed to be reduced despite their compliance with traffic laws.
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Introduction
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BACKGROUND OF STUDY
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ABSTRACT
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BACKGROUND OF THE STUDY
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ABSTRACT
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