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Design and Testing of Autonomous Steering System Implemented on a Toyota Ha:mo

Nuksit Noomwongs, Ambar Bajpai, Prin Phutthaburee, Lattapol Wongpiya, Anuparp Skulthai, Tay Zar Bhone Maung, Ye Moe Myint, Irfan Ullah, Lunchakorn Wuttisittikulkij, Muhammad Saadi

2020 International Conference on Electronics, Information, and Communication (ICEIC)(2020)

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Abstract
Recent advancements in the field of communication, control and embedded systems have triggered researchers to develop intelligent transportation system which can be ubiquitous, smart and autonomous. This paper presents the implementation of an autonomous driving car system for an ultra-small electric vehicle, branded as Toyota Ha:mo. The main objective of this work is to maximize the utilization of these available electric vehicles on campus by autonomously moving them from underutilized areas to an area where they are in high demand. Our indigenously developed system includes an Arduino based motor control system for steering, a camera and image processing subsystem for a lane detection and road sense intelligence and a global position system (GPS) module for outdoor localization. For experimental purpose, the autonomous system was installed on an electric vehicle. The results show that the autonomous electric vehicle passes the autonomous steering test for the required turning radius and achieves almost every benchmark set by Toyota. Therefore, our work provides a promising foundation for efficient utilization of resources in a campus-wide transportation system and opening new horizons for further enhancements and improvements.
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Key words
Autonomous vehicles,intelligent transportation system,control system,GPS,localization
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