Keywords: Tradable credit scheme, traffic simulation, machine learning
Team participants: Renming Liu, Carlos Lima Azevedo, Yu Jiang, Ravi Seshadri
Lead Organization: Technical University of Denmark
Historically, inefficiencies such as congestion and vehicular emissions have been generally addressed with information provision and pricing. Recently, quantity control has been under the spotlight in transportation research, leveraging from successful applications in other economic sectors, such as the communications, energy, or environmental sectors. Limited supply is in the end a scarcity problem that can be dealt with a price instrument, a quantity instrument, or a combination of both, such as tradable credit schemes (TCS). Within a TCS system, a regulator provides an initial endowment of mobility credits to all potential travelers. In order to use a transportation system, users need to spend a certain number of permits (i.e.: tariff) that could vary with the conditions/performance of the specific mobility alternative used. The permits can be bought and sold in a market that is monitored by the regulator at a price that is determined by demand and supply interactions.
In this project, we aim at leveraging the existing theoretical foundation on TCS and focus on its potential deployment and impact assessment in a realistic setting. The project will be rooted around the implementation in realistic simulation applications. Other data sources, namely from controlled experiments to be designed by the team, can be incorporated into the project to further test the developed frameworks.
Within this project, we will:
- Design and model a flexible platform (e.g., SimMobility) for testing different management scheme mechanisms;
- Formulate and develop one of the management schemes of interest, its components, and solving methods;
- Code, implement and validate for the developed platform within the context of simulation environment;
- Test the impact of different scheme designs within the developed framework;
- Benchmark and provide recommendations on the design and application of tradable credit schemes vs. congestion pricing.
- Nanyang Technological University, Zhiwei (David) Wang, https://dr.ntu.edu.sg/cris/rp/rp00618
- Massachusetts Institute of Technology, ITS Lab (Moshe Ben-Akiva, Siyu Chen), https://www.its.mit.edu/
DTU Alliance Program, https://www.dtu.dk/english/about/profile/international-collaboration/alliances-and-strategic-partnerships/nanyang-technological-university