【摘要】 随着人工智能技术在交通运输行业的广泛应用，对交通运输专业人才的培养提出更高要求，高校交通运输专业教育亟需与新兴技术深度融合。以交通运输专业人工智能类课程的改革探索为目标，从教学内容和教学方法进行改革探索，表明跨学科的课程内容改革以及讨论式教学、互动式教学等教学模式改革可帮助交通运输专业学生更好地理解人工智能类课程。以“交通基础设施智能化基础”课程为例进行实践，并对课程的反馈情况进行调查与分析，以期为交通类专业人工智能课程的改革提供实践依据和参考借鉴。更多还原

【Abstract】 With the rapid development of artificial intelligence(AI) in the transportation industry, higher education faces new challenges in training transportation professionals. Universities need to integrate emerging technologies into transportation courses. This paper explores the reform of AI-related courses for transportation majors, focusing on improvements in both course content and teaching methods. It shows that interdisciplinary content design, together with discussion-based and interactive teaching approaches, can help students better understand the courses. The course “Intelligent Transportation Infrastructure Fundamentals” is used as a case study. The paper also includes a survey and analysis of student feedback. The aim is to provide practical experience and useful references for future reforms of AI-related courses in transportation education.更多还原