Tampa, Florida
June 15, 2019
June 15, 2019
June 19, 2019
Computing and Information Technology
21
10.18260/1-2--32137
https://peer.asee.org/32137
696
Dr. Rendong Bai received his PhD degree in Computer Science from University of Kentucky in 2008. From 2007 to 2008, he worked at Eastern Kentucky University in the Department of Computer Science as a Visiting Assistant Professor. He was an Assistant/Associate Professor in the School of Technology at Eastern Illinois University from 2008 to 2018. In Fall 2018, he joined the Applied Engineering and Technology department at Eastern Kentucky University. His research interests include mobile computing, server technology, network security, multimedia and web technologies, computer-aided design and manufacturing, quality management, and renewable energy.
Dr. Wutthigrai Boonsuk is an associate professor of Applied Engineering and Technology at Eastern Illinois University. He earned his master’s and doctorate degrees in Industrial and Manufacturing System Engineering from Iowa State University. Dr. Boonsuk also received his second master’s degree in Human Computer Interaction from the same university. His research interests include 3D stereoscopic applications, Manufacturing Systems, Rapid Prototyping, Robotic and Controller Systems, Virtual Reality, and Geographic Information System (GIS). Dr. Boonsuk may be reached at wboonsuk@eiu.edu
We’re in the middle of a rapid evolution of how vehicles are operated on road. Thanks to innovations such as sensor technology, data analysis, and artificial intelligence, a growing number of companies from outside the traditional automobile industry join the race of building ultimately autonomous vehicles.
In this paper, we conduct a study on self-driving technology. We first explain the benefits of autonomous cars. The primary benefit is that they reduce accidents and save lives. There has been a long history of developing self-driving cars, from Stanford Cart in 1961 to Tesla and Google at present. The differences between Tesla and Google are mainly in two areas, computer vision technology and human car control.
Self-driving is challenging and requires a wide range of technologies, including learning the environment, tracking objects, localization, path planning, and control. We illustrate finding lane lines with computer vision and predicting the location of other vehicles using Kalman filters.
Bai, R., & Boonsuk, W., & Liu, P. P. (2019, June), Autonomous Driving and Related Technologies Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32137
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