Expanding Skill Sets for Autonomous Vehicle Repair via Fuzzy Multi-Objective Programming Based Techniques

Recently, autonomous driving technology has grown quickly. However, very little to no research has focused on the skill sets required for repairing autonomous vehicles. For students of vocational education and training (VET), how these skills can be acquired under various education goals was never studied. This research aims to cross these research gaps and derive the skills required by technical high school students in autonomous vehicles and the optimum expansion path for those skills. This study uses the fuzzy competence set expansion technique to derive the best way for technical high school students to master autonomous vehicle (AV) maintenance skills with the least amount of time and money spent. The skills derived include being able to diagnose and fix heating, ventilation, air conditioning, and rechargeable energy-storage cooling systems for AVs and being able to update software for these vehicles. The optimal expansion path commences with 'diagnosing and repairing HVAC and rechargeable energy storage cooling systems in electric vehicles,' progresses to 'executing software updates for autonomous vehicles,' and concludes with 'diagnosing and repairing air conditioning and HVAC systems.' These derived skill sets and the optimum expansion path of those skills can also be utilized as a starting point for designing new curriculum for technical high schools in the future.