The core complexities or themes of interest to the lab include:
- Dynamics: temporally evolving conditions characterize many network systems. Central among these is traffic representation which exhibits clear dynamic properties such as shockwave propagation, queuing, and link spill-over. The lab has conducted substantial work in this area through dynamic traffic assignment, time-dependent routing, and traffic analysis/simulation.
- Uncertainty: as with most complex large-scale systems, transportation networks are subjected to numerous inherent uncertainties. Both long-term, short-term and real-time stochasticities characterize transportation systems related to network supply/environment, demand, and behavior. We have pioneered work in developing methods for quantifying long-term demand and supply uncertainty (particularly with correlation among trip values) in terms of network evaluation as well as network design and signal optimization.
- Information: with the rise of Intelligent Transportation Systems (ITS), ever increasing observability, and more general information/control opportunities, it is critical to develop models which fully account for network behavior under information provision. We are pursuing this area through online routing, User Equilibrium with Recourse (UER), and asset-based wireless network modeling.
|
Numerous specific applications include:
- Dynamic Traffic Assignment
- Routing
- Network design
- Planning under uncertainty
- Travel time prediction
- Network Pricing
|