Project-based learning in a Competition of Intelligent Transport System: Knowledge Innovation Viewpoint by Actor-Network Theory

Abstract

Since 2006, the National University Students Intelligent Car Race held in China attracted tens of thousands of participants. College students use single-chip microcomputers as the core control module of the model self-driving car platform. To make the model car identify the road autonomously, the participants have to carefully arrange suitable electromagnetic and optical sensors to determine the changes in road conditions. In addition, they have to control the motor sets to drive the model car to complete the challenge optimally. The competition's critical challenge is finding the best strategy in the interdisciplinary problems of electronics, mechanics, control, and mathematics. In addition, valuable results for the competition may also emerge from the positive interaction process between the student team and the teacher group from a vocational college. From the perspective of actor-network theory (ANT), this paper explores the process of innovation of knowledge of student teams in the process of interdisciplinary problem-solving. Through project-based learning, students from different professional backgrounds such as vehicle engineering, electronic engineering, mechanical and electrical engineering, and signal engineering effectively optimize the design of autonomous vehicles. The guidance provided by teachers from different professional backgrounds also inspires students to think differently. In short, teams composed of teachers and students with different professional backgrounds effectively catalyze interdisciplinary innovation of knowledge through project-based learning and optimize the strategy of intelligent transportation competition.