The AutoDrive Challenge: Autonomous Vehicles Education and Training Issues

Bastiaan, Jennifer; Peters, Diane; Pimentel, Juan; Zadeh, Mehrdad · 2020 · OpenAlex-citations

DOI: 10.18260/1-2--33371

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Summary

This paper examines the educational and training challenges associated with the SAE/GM AutoDrive Challenge, a collegiate competition designed to prepare students for careers in autonomous vehicle (AV) development. Motivated by the automotive industry’s need for a skilled workforce amid projected STEM shortages, the study focuses on Kettering University’s participation in the three-year competition, which tasks teams with modifying a Chevrolet Bolt to achieve SAE Level 4 autonomy. The authors aim to identify the skills students acquire, evaluate the competition’s value, and determine the gaps in current engineering curricula regarding AV design. The research methodology combines a descriptive analysis of the competition structure with empirical data from student surveys. The AutoDrive Challenge involves eight universities and includes static events, technical reports, and dynamic driving tests, such as longitudinal stop-line navigation, lateral cornering, and object avoidance. At Kettering University, faculty advisors oversee a team of approximately sixty students, strictly prohibiting direct faculty involvement in vehicle design to ensure student-led engineering. To assess educational needs, the authors conducted two anonymous surveys of team members, including undergraduates and graduates from various engineering disciplines. These surveys evaluated student interest in new courses, the integration of AV topics into existing curricula, and their perceived preparedness for the industry. The findings reveal significant gaps between traditional coursework and industry requirements. Students reported that existing university courses did not adequately prepare them for the self-driving car industry, whereas participation in the AutoDrive Challenge significantly improved their readiness. Survey results indicated high interest in new courses focused on autonomous vehicle control, artificial intelligence, sensor fusion, and computer vision. Students also expressed a strong preference for integrating these topics into existing classes rather than taking standalone electives. Additionally, there was notable interest in independent studies and capstone projects related to AutoDrive, with graduate students specifically interested in thesis work. The data suggests that while students are highly motivated to enter the AV field, current educational offerings lack the interdisciplinary depth required for complex systems integration. The paper concludes that student competitions like AutoDrive provide critical practical experience that complements theoretical coursework, fostering skills in systems engineering, project management, and interdisciplinary collaboration. However, the rapid evolution of AV technologies, such as deep learning frameworks and specialized hardware, complicates curriculum design. The authors emphasize the need for universities to develop targeted educational programs that balance foundational knowledge with emerging industry standards. By forging close ties between academia and corporate sponsors, institutions can better align their training with industry needs, ensuring graduates are equipped with the specific technical and ethical competencies required for autonomous driving roles.

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