ACE055 Advanced Transportation Engineering
This is a compulsory 7,5 credits course and it is the advanced version of ACE050 Transportation Engineering and Traffic Analysis. The course includes both macroscopic and microscopic levels traffic analysis geared towards learning about traffic operations and safety. It has three components: Traffic Assignment Methodologies for Infrastructure Planning, Advanced Traffic Flow Models for Traffic Operations, and Advanced Statistics for Traffic Safety Assessment. For the first component, user equilibrium and system optimality will be taught and a commercial simulation software will be used for solving large scale transport network problems. In the second component, advanced queuing models and microscopic traffic simulations will be introduced for traffic operations. Last but not the least, advanced statistical models will be delivered in order to evaluate and enhance traffic safety. The ultimate goal of the course is to deepen the understanding of transportation discipline, learn how to practice planning, operations, and design. The students will learn about the most up to date challenges that transportation engineers face in modern society, and the contemporary tools that can be developed and used to overcome those challenges.
The course will be taught online during the Spring 2021 Semester. Please use the following link to access the course.
From the beginning until Monday of Week 5 (15 Feb 2021 inclusive)
From 18 Feb 2021 inclusive Thursday of Week 5 through to the end
After learning this subject, the students are expected to be able to:
- Conduct traffic assignment practices
- Evaluate performance of transport infrastructure
- Assess safety and efficiency aspect of intelligent transportation systems
- Design traffic control strategies for freeways and intersections
There is no textbook for this subject. Please use the handouts and tutorials that will be uploaded to PingPong.
40%: group based project, Transportation Planning of Gothenburg Region
Course Grading System for the Exam and the Whole Course
5: 90% or above
Xiaobo Qu, Professor, firstname.lastname@example.org
Ivana Tasic, Assistant Professor, email@example.com
Jie Zhu, PhD student, firstname.lastname@example.org
Ziling Zeng, PhD student, email@example.com
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