This module addresses mechanisms and strategies to model multi-modal transportation. The objectives are first to introduce concepts of population modeling. Second, it extends graph theory concepts for modeling heterogeneous transportation networks, in particular public transport networks. Mechanisms for activity and demand modeling for multimodal transportation will also be discussed. Finally, this lecture trains on best practices to apply these concepts for efficient multimodal transportation planning on vehicular traffic simulators.
Teaching and Learning Methods: Lectures and Lab sessions (group of 2 students).
Course Policies: Attendance to the Lab session is mandatory.
None.
- Basic vehicular traffic modeling
- Basic graph theory knowledge
- Basic C++ and Bash / Python knowledge
Graph Theory
- Shortest Trip Planning
- Nearest Neighbor Planning
Population Modeling and Analysis
Multi-modal transport theory
- Activity-based Modeling
- Demand Modeling
Public Transportation Planning
- Public network modeling
- Multi-modal mapping
Advanced Topic in Transport Planning
Learning outcomes:
- To be able to understand strategies and benefits of population modeling
- To be able to analyze heterogeneous transportation networks
- To be able to design activity-based modeling for multi-modal transportation
- To be able to apply these concepts for multimodal transport planning on traffic simulators
Nb hours: 21.00
Evaluation:
- Lab reports (50% of the final grade),
- Final Exam (50% of the final grade).
