TY - JOUR
T1 - Lane keeping system by visual technology
AU - Fan, Tony
AU - Liao, Gene Yeau Jian
AU - Yeh, Chih Ping
AU - Wu, Chung Tse Michael
AU - Chen, Jimmy Ching Ming
N1 - Funding Information:
Dr. Chung-Tse Michael Wu is currently an Assistant Professor at the Department of Electrical and Computer Engineering at Wayne State University (WSU), Michigan, USA. His research interests include applied electromagnetics, antennas, passive/active microwave and millimeter-wave components, RF systems and metamaterials. He received his B.S. degree from National Taiwan University (NTU) in 2006. He then received his M.S. and Ph.D. degree in the Department of Electrical Engineering, University of California at Los Angeles (UCLA) in 2009 and 2014, respectively. From September 2008 to June 2014, he worked as a graduate student researcher at the Microwave Electronics Laboratory in UCLA. In 2009, He was a summer intern in Bell Labs, Alcatel-Lucent, Murray Hills, NJ. In 2012, he was a special-joint researcher at Japan Aerospace Exploration Agency (JAXA) in Kanagawa, Japan. In 2016, Dr. Wu received National Science Foundation (NSF) Faculty Early Career Development (CAREER) Award, as well as WSU College of Engineering Faculty Research Excellence Award. He was also a recipient of 2011 IEEE Asia Pacific Microwave Conference (APMC) Student Prize and a recipient of 2013 IEEE APMC Best Student Paper Award. In addition, he received the second place award in 2014 IEEE International Microwave Symposium (IMS) student design competition. He is a Member of IEEE, IEEE-MTTs, IEEE-APS and IEEE-ComSoc.
Publisher Copyright:
© American Society for Engineering Education, 2017.
PY - 2017/6/24
Y1 - 2017/6/24
N2 - The introduction of vehicle automation, autonomy and connectivity is fundamentally changing the concept of automotive transportation. Although many of these technologies are still in development in lab, some of these technologies are already available and demonstrated by the prototypes such as Google and Toyota self-driving cars. To prepare for the future workforce needs of autonomous vehicles in the automotive industry, we develop new, technologically progressive curricula and hands-on lab as well as student project materials. This proposed "Lane Keeping System by Visual Technology" is a research and concept-proving student project that will be studied and used to develop teaching materials for the subject of vehicle automation, autonomy and connectivity. Lane Keeping System (LKS) is an advanced active safety system, which uses a front-view camera to detect lane lines and distinguish lateral deviation. It will alert drivers when there is unintentional departure from the driving lane, and then actively steer the vehicle back into the driving lane. Vehicles not connected to the infrastructure do not have real time information of their lane position on the road. A visual identification system using a camera is therefore fundamental for a vehicle to obtain the traffic information. In this student project, a webcam and a microcomputer (Raspberry Pi) are connected and mounted on a previously developed modified RC toy car where the car movements are controlled by an Arduino. The obtained images in front of the car are processed by the OpenCV software. The current goal is to identify the horizon line, the roadside lines, and vertical roadside building lines from the images and then drive the car in the "middle" of the road. The test takes place in a long hall way and the RC toy car is able to stay in the middle when moving along the hallway automatically. Student working processes of design, hardware modification, as well as the algorithm and coding procedures are presented. The project activities, the testing results, and student's learning experiences and outcomes are present in this paper.
AB - The introduction of vehicle automation, autonomy and connectivity is fundamentally changing the concept of automotive transportation. Although many of these technologies are still in development in lab, some of these technologies are already available and demonstrated by the prototypes such as Google and Toyota self-driving cars. To prepare for the future workforce needs of autonomous vehicles in the automotive industry, we develop new, technologically progressive curricula and hands-on lab as well as student project materials. This proposed "Lane Keeping System by Visual Technology" is a research and concept-proving student project that will be studied and used to develop teaching materials for the subject of vehicle automation, autonomy and connectivity. Lane Keeping System (LKS) is an advanced active safety system, which uses a front-view camera to detect lane lines and distinguish lateral deviation. It will alert drivers when there is unintentional departure from the driving lane, and then actively steer the vehicle back into the driving lane. Vehicles not connected to the infrastructure do not have real time information of their lane position on the road. A visual identification system using a camera is therefore fundamental for a vehicle to obtain the traffic information. In this student project, a webcam and a microcomputer (Raspberry Pi) are connected and mounted on a previously developed modified RC toy car where the car movements are controlled by an Arduino. The obtained images in front of the car are processed by the OpenCV software. The current goal is to identify the horizon line, the roadside lines, and vertical roadside building lines from the images and then drive the car in the "middle" of the road. The test takes place in a long hall way and the RC toy car is able to stay in the middle when moving along the hallway automatically. Student working processes of design, hardware modification, as well as the algorithm and coding procedures are presented. The project activities, the testing results, and student's learning experiences and outcomes are present in this paper.
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M3 - Conference article
AN - SCOPUS:85030528579
SN - 2153-5965
VL - 2017-June
JO - ASEE Annual Conference and Exposition, Conference Proceedings
JF - ASEE Annual Conference and Exposition, Conference Proceedings
T2 - 124th ASEE Annual Conference and Exposition
Y2 - 25 June 2017 through 28 June 2017
ER -