Open Access Open Access  Restricted Access Subscription Access

Self-Driving that Keeps Drivers in Peace of Mind - Appropriate Distance from Walls -

Chyon Hae Kim, Keigo Eto, Naoki Segawa, Tasuku Miyoshi


We address the satisfactory of the driver who is boarding on a self-driving vehicle. Even if self-driving control is perfectly safe, the driver may take anxiety caused by the duration between a vehicle and a wall. In order to reveal the boundary condition of satisfied driving, we proposed exeprimental environment and procedure. Also, we conducted a psychological experiment for 21-22 aged 6 male Japanese participants who have Japanese driving licenses using the proposed environment and procedure. As a result, the participants were satisfied when the vehicle is away from the wall more than 1.186 m at the condition of 60 km/h and 3.9 m lane width. The proposed environment and procedure are applicable to many other conditions to reveal the limitation of satisfactory about the distance between a vehicle and a wall.


safety; satisfactory in driving; self-driving; psychology

Full Text:



D. Bajpayee and J. Mathur, “A Comparative study about Autonomous Vehicle,” IEEE Inter. Conf. on Innovations in Information Embedded and Communication Systems, pp. 1-6 , 2015. CrossRef

C. Berger, A. M. M. Abdullah, and J. Hansson, “COTS-Architecture with a Real-Time OS for a Self-Driving Miniature Vehicle,” Architecting Safety in Collaborative Mobile Systems of Inter. Workshop, 2013.

N. J. Goodall, “Can You Pprogram Ethics Into a Self-Driving Car?,” IEEE Spectrum, 2016. CrossRef

D. Howard and D. Dai, “Public Perceptions of Self-driving Cars: The Case of Berkeley, California,” Annual Meeting of the Transportation Research Board, pp. 1-21, 2013.

T. Imamura, K. Itoh, Z. Zhang, and T. Miyake, “Estimation of Car Driver’s Psychology and Ability using Driving Behavior,” IEEE Inter. Conf. on Systems, Man and Cybernetics, pp. 978-983, 2007.

L. Luo, “Adaptive Cruise Control Design with Consideration of Humans’ Driving Psychology,” World Congress on Intelligent Control and Automation, pp. 2973-2978, 2014.

J. J. Martinez and C. Canudas-De-Wit, “A safe longitudinal control for adaptive cruise control and stop-and-go scenarios,” IEEE Trans. on Control Systems Technology, Vol. 15, No. 2, pp. 246-258, 2007. CrossRef

M. N. Mladenovic and M. Abbas, “Priority-based Intersection Control Framework for Self-Driving Vehicles: Agent-based Model Development and Evaluation,” Inter. Conf. on Connected Vehicles and Exop, pp. 377-384, 2014. CrossRef

K. Santhanakrishnan and R. Rajamani, “On spacing policies for highway vehicle automation,” IEEE Trans. on Intelligent Transportation Systems, Vol. 4, pp. 198-204, 2003. CrossRef

Y.-W. Seo, J. Lee, W. Zhang, and D. Wettergreen, “Recognition of Highway Workzones for Reliable Autonomous Driving,” IEEE Trans. on Intelligent transportation Systems, Vol. 16, No. 2, 2015.

Y-W Seo and R. Rajkumar, “Tracking and Estimation of Ego-Vehicle’s State for Lateral Localization,” IEEE Inter. Conf. on Intelligent Transportation Systems, pp. 1251-1257, 2014. CrossRef

N. Sümer, T. Ozkan, and T. Lajunen, “Asymmetric relationship between driving and safety skills,” Accident Analysis and Prevention, Vol. 38, pp. 703-711, 2006. CrossRef

Y. Tanaka and M. Hashimoto, “Effects of a fellow passenger robot on car drivers,” IEEE Inter. Sympo. on Robot and Human Interactive Communication, pp. 583-588, 2012. CrossRef

L. Ximin, L. Shoufeng, and Y. Zhaosheng, “Traffic Safety Oriented and User Centered Human machine Interface Design of In-vehicle Information System,” IEEE Inter. Conf. on Vehicular Electronics and Safety, pp. 491-495, 2006. CrossRef

J. Yang and J. F. Coughlin, “In-Vehicle Technology for Self-Driving Cars: Advantages and Challenges for Aging Drivers,” Inter. J. of Automotive Technology, Vol. 15, No. 2, pp. 333-340, 2014. CrossRef

J. L. Zhang and P. A. loannou,”Longitudinal control of heavy trucks in mixed traffic: Environmental and fuel economy considerations,” IEEE Trans. on Intelligent Transportation Systems, Vol. 7, No. 1, pp. 92-104, 2006. CrossRef

W. Zhong-hua, C. Xue-mei, G. Li, and C. Hongmei, “Mix effect model on the relation between braking pedal velocity and physiology,” IEEE Chinese Control and Decision Conf., pp. 3705-3707, 2009.



  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.