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Control of a Robotic Vehicle Using a Driving Simulator

Su, Jian
http://rave.ohiolink.edu/etdc/view?acc_num=ucin165953061630215

Abstract Details

2022, MS, University of Cincinnati, Engineering and Applied Science: Mechanical Engineering.
With the development of artificial intelligence and robotic technology, autonomous vehicles are becoming an important part of road traffic. By collecting and processing the data from installed sensors and cameras, autonomous vehicles navigate themselves by algorithms instead of being driven by humans. It is reported that over 90 percent of accidents are caused by human factors [1]; thus, the application of autonomous vehicles could reduce accidents significantly. In addition, autonomous technologies are based on electric vehicles system, so autonomous vehicles have higher fuel efficiency and lower carbon emission [2]. However, the popularization of autonomous vehicles requires a long period of research time, and there is still a long way to go for autonomous vehicles to replace human-driven vehicles completely. During this period, road traffic will be a mix of autonomous and human-driven vehicles, and autonomous drive technology will be developed under such situations [3]. Autonomous drive in a traffic system with mixed autonomous and human-driven vehicles requires transitioning from a simulation to a real road environment. The simulation environment is a city road sandbox model with mixed vehicles running. Test of autonomous algorithms in the early stage can be deployed to simulation to save cost and ensure safety. In this thesis, a ROS-based control method was developed to simulate a realistic human-driven vehicle used in a mixed environment. Communication algorithms and video transmission of a robotic vehicle were designed and implemented. With developed algorithms, the driver can use a simulator to drive the robotic vehicle in the city road model. For hardware, an off-the-shelf four-wheeled Raspberry Pi robotic vehicle is selected as a testing vehicle and a Logitech G29 Racing Wheel and Floor Pedals kit as the simulator. The control of the vehicle is based on ROS topic communication. The signal of the simulator of the G29 kit is extracted, processed, and published in the form of motion commands, so ROS on Raspberry Pi can subscribe to the commands and control the vehicle. Video is also transmitted through ROS topic communication from a camera on the vehicle to the computer so the real-time images can be displayed on a computer monitor/simulator monitor. Using the ROS-based control method to use a simulator to control a real robotic vehicle is a new accomplishment, and no one has done it yet. It will integrate both human-driven and autonomous-driven robots into the same ROS environment that ensures accessibility of ROS communication in the whole city road system. ROS-based control on Raspberry Pi will provide a significant number of expandable functions with necessary hardware adaptive modification of code that ensures the flexibility of robotic vehicle selection.
Janet Jiaxiang Dong, Ph.D. (Committee Member)
David Thompson, Ph.D. (Committee Member)
Ou Ma, Ph.D. (Committee Member)
92 p.
Mechanical Engineering
Robotics; ROS; Control; HHIL; Driving simulator

Recommended Citations

Citations

  • Su, J. (2022). Control of a Robotic Vehicle Using a Driving Simulator [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin165953061630215

    APA Style (7th edition)

  • Su, Jian. Control of a Robotic Vehicle Using a Driving Simulator. 2022. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin165953061630215.

    MLA Style (8th edition)

  • Su, Jian. "Control of a Robotic Vehicle Using a Driving Simulator." Master's thesis, University of Cincinnati, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=ucin165953061630215

    Chicago Manual of Style (17th edition)

ucin165953061630215
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© 2022, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.
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