The purpose of this paper is to demonstrate that latent variables, with the focus on sensation seeking concepts, incorporated in new technique of route choice modeling, improve our analyzing of route choice behavior with pre-trip travel time information. The application of a hybrid discrete choice model framework integrates a latent variable model and a route choice model by combining their mea...

Many exist studies always use Markov decision processes (MDPs) in modeling optimal route choice in stochastic, time-varying networks. However, taking many variable traffic data and transforming them into optimal route decision is a computational challenge by employing MDPs in real transportation networks. In this paper we model finite horizon MDPs using directed hypergraphs. It is shown that th...

The network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing the total travel cost in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice ...

In this work, route-choice simulations and laboratory experiments were conducted in order to evaluate the effect of feedback mechanism on decision-making under uncertainty, with and without provided information about travel times. We discuss the prediction of travellers' response to uncertainty in two route-choice situations. In the first situation travellers are faced with a route-choice probl...