The University of Melbourne
DEPARTMENT OF INFRASTRUCTURE ENGINEERING
CVEN90063 Transport System Modelling
Subject Project 2: Traffic Assignment Models
Due Date: June 10th at 9:00am
• This is an individual assignment and accounts for 50% of your final mark.
• The network and demand data files are from the Sioux-Falls network and identical to
those shared with you previously (you need to find and use Sydney network for Task 6).
• The submission should include 2 files:
1. Final report (~3000 words) in .pdf format. In this report, you need to include a
half page summary for each task (to briefly explain what your code does) and
then present the interpretation of your results after the summary.
2. A compressed file in .zip format that contain all the supporting files, including all
codes, Excel spreadsheets, data files, and your model outputs. Ensure you clearly
name/label the file for each task.
Task 1: UE Traffic Assignment – 10 pts
Find the User Equilibrium traffic assignment solution for the network of Sioux-Falls, using the
Method of Successive Averages with 250 iterations.
• Calculate the link flows and link travel times in the UE solution.
• Calculate the ratio of Volume/Capacity for all links.
• Create a dataframe with the following columns (Link ID, Link Flow, Link Travel Time,
Volume Capacity Ratio, Externality) and save the result as a CSV file.
• Report the UE total system travel time and the average travel time for all cars, and the
convergence criteria in each iteration.
Task 2: UE Application in Short-Term Planning – 10 pts
Find the (one-way) link in Sioux-Falls network that can result in maximum improvement of total
travel time (for the system) when the link is selected for a construction project with an anticipated
increase of its capacity to 150%. Solve the UE problem with the proposed link improvement
scenario using MSA for 100 iterations.
• Create a dataframe with the following columns (Link ID, Link capacity_updated, Link Flow,
Link Travel Time, Volume Capacity Ratio, Externality) and save the result as a CSV file.
• Report the estimated total time savings as the result of capacity improvements.
• Calculate the monetary equivalent of total time saving as the result of capacity
improvements, assuming VOT = $25/hr.
Task 3: SO Traffic Assignment – 10 pts
Find the System Optimal traffic assignment solution for the network of Sioux-Falls, using the
Method of Successive Averages with 250 iterations. Note: use the original capacity in this task.
• Report the link flows and link travel times in the SO solution.
• Calculate the ratio of Volume/Capacity for all links.
• Compare the marginal costs and externalities for all links in the SO solution vs the UE
solution.
• Report the SO total system travel time and the average travel time for all cars.
Task 4: Traffic Assignment with Toll – 20 pts
Find the link and its optimal toll value in Sioux-Falls network that can result in maximum total toll
collection. Assume that VOT = $25/hr and toll value can be any integer number ranging from 0 to
25$(including 25). Report the link flows and link travel times in your toll scenario, and the total
system travel time changes.
Task 5: Toll design to achieve system optimal total travel times – 20 pts
Use Sioux-Falls network and find the toll value on all links (all links tolled at the same time) that can
help us achieve the minimum system travel time (total for all vehicles). Report link toll values, link
flows and link travel times in your toll scenario, and the total system travel time improvements.
(Toll values can be any real number)
Task 6: Large-scale Shortest Path Computation – 30 pts
Find the network of Sydney in the following public database:
(https://github.com/bstabler/TransportationNetworks)
• Execute Dijkstra algorithm based on free-flow travel times in this network and report the
fastest path travel time and the path links from node 7018 to node 15163.
• For the return trip from node 15163 to node 7018, assume that link volumes are all the
same for all links in the network and equal to 2000 multiplied by a random number
between 0.5 to 0.9, report the fastest path travel time (from node 15163 to node 7018) and
the path links.
Plagiarism declaration
By submitting work for assessment I hereby declare that I understand the University’s policy
on academic integrity and that the work submitted is original and solely my work, and that I have
not been assisted by any other person (collusion) apart from where the submitted work is for a
designated collaborative task, in which case the individual contributions are indicated. I also
declare that I have not used any sources without proper acknowledgment (plagiarism). Where the
submitted work is a computer program or code, I further declare that any copied code is declared in
comments identifying the source at the start of the program or in a header file, that comments
inline identify the start and end of the copied code, and that any modifications to code sources
elsewhere are commented upon as to the nature of the modification.
