On the stochastic network equilibrium with heterogeneous choice inertia

• Heterogeneous traveler population in terms of inertial levels and knowledge structures.
• A new modeling scheme for describing cross-scenario traffic equilibria and scenario-specific disequilibria in stochastic networks.
• A variational inequality model and a simplicial decomposition algorithm.
• A tool for evaluating the impacts from choice inertia and information provision.

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 describe in this paper 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. Numerical results from a few stochastic network examples demonstrate the validity and effectiveness of our methodology in modeling the inertia phenomenon within route choice behavior and the efficacy of using traveler information systems to eliminate the inertia effect.