TY - GEN
T1 - Behavioral inertia, network equilibrium, and traveler information systems
AU - Xie, Chi
AU - Liu, Zugang
PY - 2013/12/1
Y1 - 2013/12/1
N2 - This paper presents an equilibrium modeling scheme for describing network flows formed by behaviorally inertial travelers routing in stochastic networks with a finite number of states. The network flow pattern is an aggregation result of recurrent traffic dynamics caused by varying network states. 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. This 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. Numerical results from a few stochastic network examples demonstrate the validity and effectiveness of our methodology in modeling the inertia phenomenon in route choice behavior and the efficacy of using traveler information systems to eliminate the inertia effect.
AB - This paper presents an equilibrium modeling scheme for describing network flows formed by behaviorally inertial travelers routing in stochastic networks with a finite number of states. The network flow pattern is an aggregation result of recurrent traffic dynamics caused by varying network states. 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. This 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. Numerical results from a few stochastic network examples demonstrate the validity and effectiveness of our methodology in modeling the inertia phenomenon in route choice behavior and the efficacy of using traveler information systems to eliminate the inertia effect.
UR - http://www.scopus.com/inward/record.url?scp=84894339958&partnerID=8YFLogxK
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U2 - 10.1109/ITSC.2013.6728541
DO - 10.1109/ITSC.2013.6728541
M3 - Conference contribution
AN - SCOPUS:84894339958
SN - 9781479929146
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 2113
EP - 2118
BT - 2013 16th International IEEE Conference on Intelligent Transportation Systems
T2 - 2013 16th International IEEE Conference on Intelligent Transportation Systems: Intelligent Transportation Systems for All Modes, ITSC 2013
Y2 - 6 October 2013 through 9 October 2013
ER -