This content is not included in your SAE MOBILUS subscription, or you are not logged in.
A Basic Study of a Driver's Gaze Area Detection System
ISSN: 0148-7191, e-ISSN: 2688-3627
Published March 28, 2017 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
With the improved safety performance of vehicles, the number of accidents has been decreasing. However, accidents due to driver distraction still occur, which means that there is a high need to determine whether a driver is properly looking at the surroundings. Meanwhile, with the trend toward partial automatic driving of vehicles in recent years, it is also urgently required that the state of the driver be grasped. Even if automatic driving is not installed, it is desired that the state of the driver be grasped and an application for control be performed depending on the state of the driver. Under these circumstances, we have built an algorithm that determines of the direction a driver is looking, to make a basic determination of whether or not the driver is in a state suitable for safe driving of the vehicle. In this algorithm, it is determined whether or not a driver is facing forward by using information such as face and viewing direction angles calculated from images from a grayscale camera installed on the steering column. Here, we report on this algorithm, including testing under basic conditions where test subjects gaze at various targets, in an actual vehicle in which a device operating according to this algorithm has been mounted.
CitationKogure, S., Kato, T., and Osuga, S., "A Basic Study of a Driver's Gaze Area Detection System," SAE Technical Paper 2017-01-0030, 2017, https://doi.org/10.4271/2017-01-0030.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
|[Unnamed Dataset 2]|
|[Unnamed Dataset 3]|
|[Unnamed Dataset 4]|
|[Unnamed Dataset 5]|
- National Police Agency of Japan, “Traffic accidents situation (2015).” ; http://www.e-stat.go.jp/SG1/estat/ListE.do?lid=000001150519. accessed August, 2016
- 2012 Motor Vehicle Crashes: Overview. National Highway Traffic Safety Administration, Washington, D.C., Tech. Rep., 2013
- Tawari, A., Sivaraman, S., Trivedi, M. M., Shannon, T., & Tippelhofer, M. “Looking-in and looking-out vision for urban intelligent assistance: Estimation of driver attentive state and dynamic surround for safe merging and braking”. In 2014 IEEE Intelligent Vehicles Symposium Proceedings (pp. 115-120). June, 2014.
- Laugier C., Paromtchik I. E., Perrollaz M., Yong M., Yoder J.-D., Tay C., Mekhnacha K., and Negre A.. “Probabilistic Analysis of Dynamic Scenes and Collision Risks Assessment to Improve Driving Safety” Intelligent Transportation System Magazine, IEEE, 3(4), 2011
- Montemerlo M. et al.: Junior: The Stanford Entry in the Urban Challenge, Journal of Field Robotics, 25-9, 569/597 (2008)
- Urmson C. et al.: “Autonomous Driving in Urban Environments” Boss and the Urban Challenge, Journal of Field Robotics, 25-8, 425/466 (2008)
- Ziegler1 Julius et al.: “Video Based Localization for BERTHA” Proc. of the IEEE Intelligent Vehicle Symposium, 1231/1238(2014)
- McDonald W. A., Hoffman E. R.: “Review of Relationships Between Steering Wheel Reversal Rate and Driving Task Demand, Human Factors” Vol. 22, No. 6, pp. 733-739 (1980)
- Rimini-Doering M. and Altmueller T.: “Effects of Lane Departure Warning on Drowsy Driver's Performance and State in a Simulator, Proc. Third International Driving Symposium on Human Factors in Driver Assessment” Training and Vehicle Design, pp. 88-95 (2005)
- Flores M., Armingol J. and Escalera A.: “Real-Time Warning System for Driver Drowsiness Detection Using Visual Information” Journal of Intelligent & Robotic Systems, Vol. 59, No. 2, pp. 103-125 (2010)
- Ford Motor Company: Driver Alert, http://technology.fordmedia.eu/documents/newsletter/FordTechnologyNewsletter082010.pdf
- Krajewski, J., Sommer, D., Trutschel, U., Edwards, D., & Golz, M. “Steering wheel behavior based estimation of fatigue. In Proceedings of the Fifth International Driving,” Symposium on Human Factors in Driver Assessment, Training and Vehicle Design (pp. 118-124), June, 2009.iv)
- Takei, Y., Yoshimi F., "Estimate of driver's fatigue through steering motion." 2005 IEEE international conference on systems, man and cybernetics. Vol. 2. Ieee, 2005.
- Kogure,S., Sakata,T., Sacha,V., “Driver’s drowsiness and non-constraint pulsation estimation,” presented at ITS world congress 2015, France, October 5-9, 2015
- Fletcher L., Loy G., Barnes N., and Zelinsky A.. “Correlating driver gaze with the road scene for driver assistance systems” RAS, 52(1), 2005
- Lex, F., Philipp, L., et al., “Driver Gaze Region Estimation Without Using Eye Movement,” IEEE Intelligent Systems, 2016
- Tawari, Ashish, and Trivedi Mohan M.. "Robust and continuous estimation of driver gaze zone by dynamic analysis of multiple face videos." 2014 IEEE Intelligent Vehicles Symposium Proceedings. IEEE, 2014.
- Fletcher, Luke, and Zelinsky Alexander. "Driver inattention detection based on eye gaze-Road event correlation." The international journal of robotics research 28.6 (2009): 774-801.
- Berndt H., Emmert J., and Dietmayer K.. “Continuous driver intention recognition with hidden markov models” In IEEE ITSC, 2008.
- Kuge, N., Yamamura, T., Shimoyama, O., and Liu, A., "A Driver Behavior Recognition Method Based on a Driver Model Framework," SAE Technical Paper 2000-01-0349, 2000, doi:10.4271/2000-01-0349.
- PECH, Timo; LINDNER, Philipp; WANIELIK, Gerd. “Head tracking based glance area estimation for driver behaviour modelling during lane change execution” In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC). IEEE, 2014. p. 655-660.
- DONG, Yanchao, et al. “Driver inattention monitoring system for intelligent vehicles”: A review. IEEE transactions on intelligent transportation systems, 2011, 12.2: 596-614.
- LEE, Sung Joo, et al. “Real-time gaze estimator based on driver's head orientation for forward collision warning system” IEEE Transactions on Intelligent Transportation Systems, 2011, 12.1: 254-267.
- Noaki, K., Osuga, S. et al., “Safety effect of eye closure alarm on drowsy drivers in real driving environment,” presented at ITS world congress 2015, France October 5-9, 2015
- Renewable Resource Data Center, “Reference Solar Spectral Irradiance: Air Mass 1.5” http://rredc.nrel.gov/solar/spectra/am1.5/ASTMG173/ASTMG173.html. accessed August, 2016