MATEC Web Conf.
Volume 90, 2017The 2nd International Conference on Automotive Innovation and Green Vehicle (AiGEV 2016)
|Number of page(s)||10|
|Published online||20 December 2016|
Real time emergency auto parking system in driver lethargic state for accident preventing
1 Faculty of Engineering Technology, Universiti Malaysia Pahang, 26300 Kuantan, Pahang, Malaysia
2 Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, 26300 Kuantan, Pahang, Malaysia
* Corresponding author: firstname.lastname@example.org
This paper is presenting a safety driving and accident preventing system which uses a vision sensor to detect driver drowsiness and lethargic states. The system notifies the driver in dangerous situations. Moreover, in case the driver is unable to conduct safe driving, emergency parking system is to be activated. The system comprises two stages. First is a drowsiness detection stage which uses a smartphone or a tablet computer as a processing unit. The second stage is the vehicle emergency parking control system which uses a microcontroller unit (MCU). The MCU is connected to an alarm system, hazard lights and a vehicle control interface. The experiment results showed realistic real time responses. Drowsiness detection processing time average is about 480 ms / frame. Alarming system is responding perfectly within 500 ms. Simulation results illustrate the effectiveness of the developed schemes for the auto parking system in real time. The average time from drowsiness detection to fully parking, if the vehicle is moving at the speed of 100 km/s, is about 15s.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.