Modelling Daily Tours Scheduling Dimensions Using Stochastic Dynamic User Equilibrium Approach

In this paper, a model is presented for the scheduling dimensions of daily tours. The model addresses activity departure times, durations, sequence and route choice along with time-varied network congestion. This model can be useful in understanding how people actually change their travel patterns in order to cope with congestion. The model is formulated as a fixed point problem under stochastic setting that brings the system in stochastic dynamic user equilibrium. The model also considers multiple user classes in such a manner that each user class performs a different tour in a day. Utility of an activity participation is based on two major components: time-of-day preference of an individual and activity satiation effect. The disutility of travel is primarily based on travel time, which is obtained using a macroscopic dynamic traffic loading model. Results of two numerical experiments are presented to show the proposed model’s functionality, convergence pattern and application in different scenarios. The findings from these experiments suggest that the proposed model is able to converge at the equilibrium solution, but that other solution algorithms should be tested to increase efficiency.