Integrated traffic-transit stochastic equilibrium model with park-and-ride facilities
mode - mass transit, mode - park and ride, planning - integration, land use - impacts
Transit equilibrium, Traffic equilibrium, Stochastic models, Congested networks, Park-and-ride
We propose an Integrated Stochastic Equilibrium model that considers both private automobile traffic and transit networks to incorporate the interactions between these two modes in terms of travel time and generalized costs. In addition, in the general version of the model, travelers are allowed to switch from personal vehicles to mass transit at specific locations in a park-and-ride scheme. The assignment for traffic equilibrium is based on the Markovian Traffic Equilibrium model of Baillon and Cominetti (2008), whereas the equilibrium of the transit network is represented by the Stochastic Transit Equilibrium model of Cortés et al. (2013). Stochastic travel decisions are made at the node level, thereby avoiding the enumeration of routes or strategies and incorporating various perception and uncertainty issues. We propose a Method-of-Successive-Averages algorithm to calculate an Integrated Stochastic Equilibrium and conduct numerical experiments to highlight the effect of stochasticity on equilibrium flows and travel times. Our experiments show that higher stochasticity implies greater dispersion of equilibrium flows and longer expected travel times. Results on a real network with mode combination and park and ride facilities provide insights regarding the use of park and ride in terms of number and location, potential modal share of the combined mode option under different circumstances, and travel time impact due to the implementation of such park and ride facilities in a real setting.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Pineda, C., Cortés, C.E., Jara-Moroni, P., & Moreno, E. (2016). Integrated traffic-transit stochastic equilibrium model with park-and-ride facilities. Transportation Research Part C: Emerging Technologies, Vol. 71, pp. 86–107.