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Validating the results of a route choice simulator
RL asserts that decision makers’ behaviors are moved towards the direction of random choice due to the environmental uncertainty .
Stochastic models mainly focus on the probability distribution of flow states [6, 7].
They found that the network flow does not necessarily converge to the user equilibrium (UE) and travelers’ cognitions of each route do not become homogeneous by learning [12–14]. assumed that each traveler used a disutility function to perceive travel time and schedule delay for evaluating the alternative travel choices, and then chose an alternative route according to the utility maximization principle .
Chen and Mahmassani modeled travelers’ leaning process by using Bayesian theory and an agent-based simulation framework to study networks’ dynamic properties .
In some literatures, traffic dynamics are modeled as continuous time processes [3, 4].
However, it is not reasonable to adjust traffic flow continuously due to travelers’ activities constraints.