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.
CITATION STYLE
Fan, T., Liao, G. Y. J., Yeh, C. P., Wu, C. T. M., & Chen, J. C. M. (2017). Lane keeping system by visual technology. In ASEE Annual Conference and Exposition, Conference Proceedings (Vol. 2017-June). American Society for Engineering Education. https://doi.org/10.18260/1-2--28604
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