Analysis of Driver Gaze and Attention to Traffic Signs
-
Published:2022-04-16
Issue:
Volume:2022
Page:1-13
-
ISSN:2042-3195
-
Container-title:Journal of Advanced Transportation
-
language:en
-
Short-container-title:Journal of Advanced Transportation
Author:
Shabani Shabnam1ORCID,
Beauchemin Steven1ORCID,
Bauer Michael1ORCID
Affiliation:
1. Department of Computer Science, The University of Western Ontario, London N6A5B7, Canada
Abstract
A driver’s actions and intent can be factors in enabling advance driver assistance systems (ADASs) to assist drivers and avoid accidents. A driver’s gaze can provide insight into the driver’s intent or awareness of situations. Knowing that a driver gazed at a traffic sign or missed a traffic could provide indications of whether the driver is alert to impending changes in the driving environment, such as curves and stop signs. For ADASs to determine the importance of a driver seeing or missing a sign, it is important to understand the driving environment and situation. A first step is to understand what signs drivers do see or miss while driving. This contribution presents the results of analyzing driving sequences to assess traffic signs that drivers may or may not have gazed upon. The results suggest that drivers may miss 20% of traffic signs though the percentage varies depending on the type of sign. The analysis uses image sequences of the driving environment and gazes data captured during driving. The methods used in our analysis included determining whether a driver’s gaze has fallen on the image of a traffic sign or not and subsequently determining signs missed during driving. The methods presented can be useful in other scenarios involving the analysis of driver gaze and have implications for the design of future ADASs and for understanding of driver gaze and awareness.
Funder
National Science and Engineering Research Council of Canada
Publisher
Hindawi Limited
Subject
Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering
Reference41 articles.
1. Determinants of Eye-Fixation Duration
2. At 120msec yu can spot the animal but you don’t yet know it’s a dog;C.-T. Wu;Journal of Cognitive Neuroscience,2014
3. Roadlab: an in-vehicle laboratory for developing cognitive cars;S. Beauchemin
4. Assessment of driver’s attention to traffic signs through analysis of gaze and driving sequences;S. Shabani
5. Driver Inattention Monitoring System for Intelligent Vehicles: A Review
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Real-time Road Signs Detection and Recognition for Enhanced Road Safety;2023 15th International Conference on Innovations in Information Technology (IIT);2023-11-14