Course Overview: This is an English course that systematically teaches the theory of sustainable transportation technologies and their applications in the field of transportation engineering. As an elective, professional course in engineering, this course serves as a bridge between the theory of smart transportation and sustainable transportation technologies and the practice of transportation engineering. The role of analytical methods, analytical thinking, and applications in the field of engineering is an important theoretical practice course that offers methodology framework and worldview.

Course Objective: Through the learning of this course, the engineering students will establish the view of transportation engineering in the era of sustainable development, the basic thinking and theoretical methods of big data in sustainable transportation engineering, and fully and systematically master data-based green sustainable transportation engineering, with the ability of preliminary analysis and application of carbon emission in multimodal transportation, Mobility-as-a-Service and Connected and Autonomous Vehicles, and traffic engineering data and modeling methods. Integrating the development trend of big data and cutting-edge sustainable development technologies in the field of transportation engineering into the teaching, students can keep up with the development pulse of the transportation industry and the trend of green sustainable development. 

Major Content: This course primarily offers the methods and working procedures of sustainable transportation technologies and practical applications of system engineering needed to acquire, mine, analyze, and apply to solve traffic engineering problems. It also covers discussion, case analysis, extracurricular exercises, and course design. The main contents include: (1) Introduction to Sustainable Transportation and Related Supporting Technologies; (2) Multimodal Transportation System; (3) Traffic Prediction and Traffic Big Data Mining; (4) Modeling and Analysis of Transportation Carbon Emissions; (5) Frontier Technologies and Applications of Green Sustainable Transportation.

Relevant SDGs: SDG 7, SDG 9, SDG 11

1. Traffic prediction and data modeling methods in sustainable transportation; 
2. Calculation of carbon emission in multimodal transportation;
3. Frontier technologies in sustainable transportation, include but not limited to discussions and analytics of Mobility-as-a-Service and Connected and Autonomous Vehicles;
4. Construction and management of green sustainable transportation.

Lecture, tutorial, discussion and seminar

1. Attendance: 20%;
2. Group presentation: 60%;
3. Final program summary: 20%.

None.

Dr. Jie Xue: J.Xue@sjtu.edu.cn