Matching Items (2)
Description

A robust autopilot control system for a ground vehicle was designed, fabricated, and implemented on a remote control car. The autopilot system consists of navigation, guidance, and three controller subsystems. The autopilot’s hardware subsystems are an Arduino processor, GPS receiver, 9 DOF inertial measurement system, and an SD card data

A robust autopilot control system for a ground vehicle was designed, fabricated, and implemented on a remote control car. The autopilot system consists of navigation, guidance, and three controller subsystems. The autopilot’s hardware subsystems are an Arduino processor, GPS receiver, 9 DOF inertial measurement system, and an SD card data logger. A complete system simulation was developed and used to verify the integrated design and algorithms, prior to field testing. The simulation results indicated the system performs as designed, with no anomalous behaviors observed. Simulations were also used to assess and verify each of the three controllers’ robustness qualities. The complete hardware system was field tested and verified fully functional against complex mission scenarios. The system performed as designed, with no anomalous behaviors observed. The system performed successfully in the presence of external disturbances (e.g., rocks, holes, dirt piles in the vehicle’s path), which demonstrated and verified the design is robust. Additional robustness testing consisted of doubling the vehicle’s polar moment of inertia and verifying this did not have any adverse effects on system performance. All the planned tasks were completed and the project’s objectives were met.

ContributorsMarino, Michael (Author) / Takahashi, Timothy (Thesis director) / Singh Grewal, Anoop (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-12
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Description
As autonomous vehicle development rapidly accelerates, it is important to not lose sight of what the worst case scenario is during the drive of an autonomous vehicle. Autonomous vehicles are not perfect, and will not be perfect for the foreseeable future. These vehicles will shift the responsibility of driving to

As autonomous vehicle development rapidly accelerates, it is important to not lose sight of what the worst case scenario is during the drive of an autonomous vehicle. Autonomous vehicles are not perfect, and will not be perfect for the foreseeable future. These vehicles will shift the responsibility of driving to the passenger in front of the wheel, regardless if said passenger is prepared to do so. However, by studying the human reaction to an autonomous vehicle crash, researchers can mitigate the risk to the passengers in an autonomous vehicle. Located on the ASU Polytechnic campus, there is a car simulation lab, or SIM lab, that enables users to create and simulate various driving scenarios using the Drive Safety and HyperDrive software. Using this simulator and the Window of Intervention, the time a driver has to avoid a crash, vital research into human reaction time while in an autonomous environment can be safely performed. Understanding the Window of Intervention is critical to the development of solutions that can accurately and efficiently help a human driver. After first describing the simulator and its operation in depth, a deeper look will be offered into the autonomous vehicle field, followed by an in-depth explanation into the Window of Intervention and how it is studied and an experiment that looks to study both the Window of Intervention and human reactions to certain events. Finally, additional insight from one of the authors of this paper will be given documenting their contributions to the study as a whole and their concerns about using the simulator for further research.
ContributorsSalceda, Rhiannon (Co-author) / Baratti, Alexander (Co-author) / Gaffar, Ashraf (Thesis director) / Gonzalez Sanchez, Javier (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05