Course syllabus
Course-PM
ACE055 ACE055 Advanced transportation engineering lp3 VT24 (7.5 hp)
Course is offered by the department of Architecture and Civil Engineering
Course Description
This is a 7,5 credits course and it is the advanced version of ACE050 Transportation Engineering and Traffic Analysis. The course focuses on some of the most practical problems and technologies. It has three components: Transportation Planning, Queue Models, and Path-finding & Vehicle Routing models. For the first component, transport planning models will be taught and commercial simulation software will be used for solving large-scale transport network problems. Such competence is crucial for consulting companies as well as regional and city offices. In the second component, advanced queuing models will be introduced for traffic operations. Queue estimation is the foundation of modern traffic system performance analysis and is thus highly desired by engineering and operational offices, such as Trafikverket in Sweden. Last but not the least, path-finding and vehicle routing algorithms will be introduced and practiced in a group project. The ultimate goal of the course is to deepen the understanding of transportation discipline, learn how to practice planning, estimation, and optimization. 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.
Schedule
Time and classrooms: TimeEdit
Schedule in PDF: Teaching schedule for ACE055 - 2024 updated.pdf
Course Objectives
After this course, the students are expected to be able to:
- Conduct traffic assignment practices
- Evaluate the performance of transport infrastructure from queue perspectives
- Find the shortest path efficiently and optimally
- Design vehicle routing trajectories for passengers, goods, and vehicles.
Learning materials
There is no exclusive textbook for this subject. Please use the slides and tutorials that will be uploaded to Canvas. The references (see below) could also be helpful for learning and getting more practice.
Transportation planning: Transportation Planning Handbook 4th Edition by ITE (Institute of Transportation Engineers) (Author), Michael D. Meyer (Author) https://silo.tips/download/the-four-step-model-uci-its-wp-michael-g-mcnallyLinks to an external site.Links to an external site.
Discrete Choice Analysis: Theory and Application to Travel Demand https://mitpress.mit.edu/books/discrete-choice-analysisLinks to an external site.Links to an external site.
Traffic assignment in large networks: GitHub - ZhengLi95/User-Equilibrium-Solution: Program for obtaining the user equilibrium solution with Frank-Wolfe Algorithm in urban traffic assignmentLinks to an external site.Links to an external site.
Shockwave theory: Introduction to Traffic Flow Theory. Victor L. Knoop. https://victorknoop.eu/research/book/Knoop_Intro_traffic_flow_theory_edition2.pdf Links to an external site.Links to an external site.
Queue model: Principles of Highway Engineering and Traffic Analysis. Fred L. Mannering, Scott S. Washburn
VRP: Vehicle Routing Problems, Methods, and Applications. Paolo Toth, Daniele Vigo. https://epubs.siam.org/doi/pdf/10.1137/1.9781611973594.fm Links to an external site.Links to an external site.
Assessment
10%: In-course exercise (on 3-5 random days)
60%: Two group-based projects (25% for project one, and 35% for project two)
30%: Homework
Note that there will be bonus points that you can get in lectures.
Course Grading System
Fail: 0-59
3: 60-75
4: 76-90
5: 91 or above
Instructors
Dr. Jiaming Wu, Researcher, jiaming.wu@chalmers.se (Examiner and Contact person)
Dr. Kun Gao, Assistant Professor, gkun@chalmers.se
Dr. Sunney Fotedar, Postdoc, sunney@chalmers.se
Teaching assistant
Dr. Sunney Fotedar, Postdoc, sunney@chalmers.se
Student Representatives
Elin Blad elin_blad@hotmail.com
Shi Chen nbcs99@hotmail.com
Riham Ebrahim rihamebrahim00@gmail.com
Victor Hansson victor.hansson00@gmail.com
Anton Pehrsson anton.pehrsson@hotmail.com
Course summary:
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