Zhihang Liu, Jieun Lee, J. Kuwana, Huiping Zhou, M. Itoh
{"title":"Investigating Effects of Assistance Systems For Visually Impaired Drivers\n at Preventing Traffic Accidents","authors":"Zhihang Liu, Jieun Lee, J. Kuwana, Huiping Zhou, M. Itoh","doi":"10.54941/ahfe1002819","DOIUrl":null,"url":null,"abstract":"Visual field defects (VFD) are closely associated with driver hazard\n perception. Drivers with advanced VFD are more likely to be involved in\n traffic accidents than healthy-sighted drivers even though they apply extra\n movements to overcome the defects. Given difficulties in dealing with\n particular situations, such as finding traffic signals, machinery assistance\n is necessary for improving driving safety. However, it has been less\n explored that which assistance systems would be helpful for visually\n impaired drivers in which traffic situations. To have a better understanding\n of driving with VFD and provide a safer traffic environment for drivers with\n advanced VFD, this study aimed to investigate effects of three driver\n assistance systems on reducing traffic accidents regarding several traffic\n situations. Methods:A driving simulator experiment using 66 healthy-sighted\n drivers generated advanced VFD on a screen for all simulations. This study\n designed a Baseline condition and three assistance systems based on\n time-to-collision (TTC) in hazardous events: automatic braking (AB; TTC =\n 0.8s) and giving voice guidance about driver behavior to cope with\n encountering situations. Two guidance systems were presented in different\n alert timings (VGEarly; TTC = 4s, VGLate; mean TTC = 2.81s). We classified\n 29 hazardous events into four categories: traffic signals, oncoming\n right-turning cars, objects that appear from driver’s right and left sides,\n then counted the number of traffic accidents. Results:Data provided that all\n assistance systems showed the lower number of accidents than the Baseline.\n Whereas drivers in the Baseline were not able to find traffic signals due to\n the defect, no accident cases related to the situation were observed in the\n assistance system conditions. When an oncoming car turned to the right,\n drivers in the VGEarly showed the lowest accident rate among all conditions.\n The AB led the great number of accidents in the oncoming car situation but\n yielded no accidents with hazards approaching from the right. Results showed\n that both VG systems were more likely to reduce the accidents with hazards\n from the left than the AB. More specifically, the VGEarly decreased the\n accident rate by approximately 15% more than the VGLate.Discussions:This\n study attempted to figure out which system is effective for visually\n impaired drivers in which traffic situation. Interestingly, the effect\n depended on situations. For example, the AB led no accidents when\n encountering objects from the right side unlike the VG systems. The VGLate\n had a potential of reducing accidents, but the VGEarly more contributed to\n reducing accidents rather than the VGLate. Because VFD led failure in driver\n perception that is a very initial stage of information processing, in\n general, VGEarly is considered to produce appropriate performance. The\n current study is limited to investigating accident rates, thus next study\n should perform further analyses of driver response that can provide two-way\n feedback between the system and the driver. Despite the limitation, the\n present study found that assistance timings and traffic situations are\n critical factors influencing system design for visually impaired drivers.\n Empirical findings are expected to provide insights into practical\n assistance designs for driving with VFD.","PeriodicalId":269162,"journal":{"name":"Proceedings of the 6th International Conference on Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems, February 22–24, 2023, Venice, Italy","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems, February 22–24, 2023, Venice, Italy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1002819","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Visual field defects (VFD) are closely associated with driver hazard
perception. Drivers with advanced VFD are more likely to be involved in
traffic accidents than healthy-sighted drivers even though they apply extra
movements to overcome the defects. Given difficulties in dealing with
particular situations, such as finding traffic signals, machinery assistance
is necessary for improving driving safety. However, it has been less
explored that which assistance systems would be helpful for visually
impaired drivers in which traffic situations. To have a better understanding
of driving with VFD and provide a safer traffic environment for drivers with
advanced VFD, this study aimed to investigate effects of three driver
assistance systems on reducing traffic accidents regarding several traffic
situations. Methods:A driving simulator experiment using 66 healthy-sighted
drivers generated advanced VFD on a screen for all simulations. This study
designed a Baseline condition and three assistance systems based on
time-to-collision (TTC) in hazardous events: automatic braking (AB; TTC =
0.8s) and giving voice guidance about driver behavior to cope with
encountering situations. Two guidance systems were presented in different
alert timings (VGEarly; TTC = 4s, VGLate; mean TTC = 2.81s). We classified
29 hazardous events into four categories: traffic signals, oncoming
right-turning cars, objects that appear from driver’s right and left sides,
then counted the number of traffic accidents. Results:Data provided that all
assistance systems showed the lower number of accidents than the Baseline.
Whereas drivers in the Baseline were not able to find traffic signals due to
the defect, no accident cases related to the situation were observed in the
assistance system conditions. When an oncoming car turned to the right,
drivers in the VGEarly showed the lowest accident rate among all conditions.
The AB led the great number of accidents in the oncoming car situation but
yielded no accidents with hazards approaching from the right. Results showed
that both VG systems were more likely to reduce the accidents with hazards
from the left than the AB. More specifically, the VGEarly decreased the
accident rate by approximately 15% more than the VGLate.Discussions:This
study attempted to figure out which system is effective for visually
impaired drivers in which traffic situation. Interestingly, the effect
depended on situations. For example, the AB led no accidents when
encountering objects from the right side unlike the VG systems. The VGLate
had a potential of reducing accidents, but the VGEarly more contributed to
reducing accidents rather than the VGLate. Because VFD led failure in driver
perception that is a very initial stage of information processing, in
general, VGEarly is considered to produce appropriate performance. The
current study is limited to investigating accident rates, thus next study
should perform further analyses of driver response that can provide two-way
feedback between the system and the driver. Despite the limitation, the
present study found that assistance timings and traffic situations are
critical factors influencing system design for visually impaired drivers.
Empirical findings are expected to provide insights into practical
assistance designs for driving with VFD.