A Multi-class Paired Combinatorial Logit Traffic Assignment Model for Assessing Benefits of Travelers Information Systems in Transportation Networks

Limited capacity of transportation infrastructures for development of new facilities and expansion of the capacity of the current facilities, in addition to the high cost of so many supply management policies, whether in the supplier’s or the transportation services user’s view, suggest to the transportation planners the fundamental necessity of referring to demand management policies. The growing rate of implementing travel time information systems, in order to enhance the performance and level of service within transportation networks, has stimulated planners to generate more sensitive models with capability of quantitatively assessing the benefits of introducing traveler information systems. A superiority of stochastic approach of traffic assignment is its higher flexibility in modeling commute behaviors than a deterministic model provides. In order to demonstrate this potential flexibility, we have suggested a multi-class version of stochastic traffic assignment with paired combinatorial logit route choice kernel—one of the most advanced discrete choice models applied in network analysis—being able to evaluate benefits of serving transportation networks by traveler information systems.