Stochastic Network Equilibrium with Inertial Behaviors by Prof. Chi Xie
Date: Tuesday, 10 June 2014
Venue: Civil & Environmental Engineering Building H20, Ground Floor, Room G8
Time: 2:00 – 3:00pm
Guest Speaker: Dr Chi Xie,B. Eng, M. Eng, MS, PhD, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiaotong University
Dr. Chi Xie obtained his Ph.D. in Transportation Systems Engineering at Cornell University in 2008. He is currently a Professor in the School of Naval Architecture, Ocean and Civil Engineering at Shanghai Jiao Tong University and an Adjunct Professor in the Division of Logistics and Transportation at Tsinghua University. His research interests span various research topics in the general transportation and logistics field, including transportation network analysis and control, transportation infrastructure management, transportation emergency and risk management, travel demand analysis and forecasting, and intelligent transportation systems. His recent research focus is on the development of new network flow and travel demand models for describing future urban transportation networks that serve electric vehicles and new modeling methods for analyzing advanced traveler information systems. Dr. Xie is a 2012 recipient of the prestigious Young Talent Award granted by the China Recruitment Program of Global Experts. At present, he is visiting the Research Centre for Integrated Transport Innovation at University of New South Wales.
Abstract :
Uncertainties or variations associated with both transportation supplies and travel demands seem inherently natural and may arise in infinite varieties. Numerous evidences show that traffic network flows vary with changing network conditions and demand rates over time. Although the resulting traffic network flows vary from one scenario to another (or from one period to another), they are not mutually separate and uncorrelated, since the traffic flow entities—individual travelers—experience multiple network scenarios (or periods) and their routing decisions are in general a synthetic result of their long-term learning process over different network states. Understanding the underlying correlation through varying traffic networks is critical to describing and evaluating traffic dynamics caused by scenario-to-scenario (or period-to-period) system supply and demand variations.
As an alternative effort for quantifying recurrent traffic dynamics caused by network variations and analyzing the impact on the network performance from information provision, we introduce in this talk a new equilibrium modeling scheme for stochastic networks with a finite number of states, which takes into account the behavioral inertia. A finite-dimensional variational inequality model is formulated to describe the cross-state equilibrium conditions among heterogeneous travelers with different inertial degrees and knowledge structures. Our model allows for traveler’s partial understanding and inertial effect in perceiving varying network conditions and provides a different perspective (from existing stochastic and Markovian network equilibrium approaches) to describe traffic flow variations across multiple network scenarios. A disaggregate simplicial decomposition algorithm is suggested to solve the variational inequality problem.
Hosted by:
Research Centre for Integrated Transport Innovation (rCITI)
School of Civil and Environmental Engineering & Computer Science and Engineering
