Do Statistics Show Differences between Distance Estimations of 3D Objects in the Traffic Environment Using Glances, Side View Mirrors, and Camera Display?

The driver’s task in traffic is to evaluate traffic situations and act in accordance with the estimate. One of the most common causes of road crashes is “incorrect estimated of the traffic situation”. Correct perception of surroundings is one of the prerequisites for safe and successful driving. To...

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Bibliographic Details
Published in:Mathematics (Basel) Vol. 11; no. 5; p. 1258
Main Authors: Trifunovic, Aleksandar, Ivanisevic, Tijana, Cicevic, Svetlana, Simovic, Sreten, Vuksic, Vedran, Slovic, Živana
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-03-2023
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Summary:The driver’s task in traffic is to evaluate traffic situations and act in accordance with the estimate. One of the most common causes of road crashes is “incorrect estimated of the traffic situation”. Correct perception of surroundings is one of the prerequisites for safe and successful driving. To investigate the mentioned issue, the authors of this paper conducted an experimental study with the aim of determining what affects the estimation of the object distance. In contrast to previous studies known from the available literature, our study presents experimental research of the estimated distance of 3D stimuli in three environments by direct observation, a rear-view mirror, and a camera display in a vehicle. One-hundred-and-sixty-four participants participated in the experiment. The research results show statistically significant differences in the estimation of the distance of 3D objects for different colors. Participants, for the largest number of stimuli, best estimate the distance from direct observation than through the rear-view mirror, while they make the most mistakes when estimating the distance of 3D objects using the camera display in a vehicle. On the other hand, in all described conditions, the respondents estimated the distance to the blue and green objects with the most significant errors.
ISSN:2227-7390
2227-7390
DOI:10.3390/math11051258