Author(s)

Xiaobing Peng ¹, Zundong Zhang ¹

Affiliation(s)

¹ North China University of Technology, Beijing, China

Corresponding Author

Xiaobing Peng

ABSTRACT

With the continuous development of automation research, automatic driving has become the trend of The Times. In practice, the driver can relax during driving and enter the state of breaking out of the control loop. However, due to the technical limitations of autonomous driving, the driver is required to take over the vehicle to deal with sudden dangerous situations. Therefore, we conducted a driving simulator experiment to analyze the eye movement behavior and take-over performance of the driver before and after taking over the vehicle in the state of off-loop. The operational response of drivers to emergencies after the release of take-over request (TOR) was used to measure take-over performance. Eye-movement behavior parameters of drivers in take-over process were obtained by tracking eye-movement behavior with eye tracker. At the same time, uc-WinRoad, a virtual reality software, was used to obtain the driver's reaction time and evaluate the quality of the control.

KEYWORDS

Conditional Autopilot, Takeover Request, Eye Movement Parameters, Time Budget, Quality of Taking Over

CITE THIS PAPER

Xiaobing Peng, Zundong Zhang, Takeover Quality Assessment and Eye Movement Behavior Analysis for Limited Autonomous Vehicle. Advances in Computer, Signals and Systems (2022) Vol. 6: 21-30. DOI: http://dx.doi.org/10.23977/acss.2022.060403.

REFERENCES

[1] Hu Xinghua; Zheng Mintanyu. Research Progress and Prospects of Vehicle Driving Behavior Prediction [J]. World Electric Vehicle Journal, 2021.
[2] Ziyan Chen; Shiguo Liu. China's self-driving car legislation study [J]. Computer Law & Security Review, 2021.
[3] Yang J, Coughlin J F. In-vehicle technology for self-driving cars: Advantages and challenges for aging drivers [J]. International Journal of Automotive Technology, 2014, 15(02):333–340.
[4] Kim H S, Yoon S H, Kim M J, et al. Deriving future user experiences in autonomous vehicle [C]. New York: Association for Computing Machinery, 2015:112–117.
[5] Ive H P, Sirkin D, Miller D, et al. “Don’t make me turn this seat around!” Driver and passenger activities and positions in autonomous cars [C]. New York: Association for Computing Machinery, 2015:50-55.
[6] Chiara Lucifora; Giorgio Mario Grasso; Pietro Perconti; Alessio Plebe Moral reasoning and automatic risk reaction during driving [J]. Cognition, Technology & Work, 2021.
[7] Helen E. Monkhouse; Ibrahim Habli; John McDermid an enhanced vehicle control model for assessing highly automated driving safety [J]. Reliability Engineering & System Safety, 2020.
[8] Lentin Joseph; Amit Kumar. Mondal Autonomous Driving and Advanced Driver-Assistance Systems (ADAS): Applications, Development, Legal Issues, and Testing [B]. 2021.
[9] Francesco Bella, Roberta Russo. A Collision Warning System for rear-end collision: a driving simulator study [J]. Procedia - Social and Behavioral Sciences, 2011, 20(2011):676-686.
[10] Moritz Körber, Christian Gold, David Lechner, et al. The influence of age on the take-over of vehicle control in highly automated driving [J]. Transportation Research Part F:Traffic Psychology and Behaviour,2016,39(2016):19-32.
[11] Zeeb K, Buchner A, Schrauf M. What determines the take-over time? An integrated model approach of driver take-over after automated driving [J]. Accident Analysis and Prevention, 2015, 78(2015):212–221.
[12] Anna Feldhütter, Gold C, Schneider S, et al. How the duration of automated driving influences take-over performance and gaze behaviour [C]. Berlin: Springer, 2016, 309-318.

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