Abstract
In this paper we present a stochastic route choice model for transit networks that explicitly addresses route correlation due to overlapping alternatives. The model is based on a multi-objective mathematical programming problem, the optimality conditions of which generate an extension to the Multinomial Logit models. The proposed model considers a fixed point problem for treating correlations between routes, which can be solved iteratively. We estimated the new model on the Santiago (Chile) Metro network and compared the results with other route choice models that can be found in the literature. The new model has better explanatory and predictive power that many other alternative models, correctly capturing the correlation factor. Our methodology can be extended to private transport networks.
Highlights
The present study formulates a new route choice model for public transport networks that features significant innovations compared to existing models
The analysis focuses on the morning and evening peak periods (7 am to 9 am and 6 pm to 8 pm) when approximately
A new transportation network route choice model was developed that explicitly incorporates the phenomenon of correlations between routes
Summary
The present study formulates a new route choice model for public transport networks that features significant innovations compared to existing models. The proposed model is Entropy 2014, 16 based on a multi-objective mathematical programming problem and its respective scalarized single-objective problem. The multi-objective problem considers the exogenous cost functions of the network, entropy of the route choice, and the covariance matrix for the route flows. A traditional approach to defining the route choice process, and the subsequent traffic equilibrium, is to assume a deterministic behavior. This deterministic equilibrium usually states optimality conditions, such as minimizing transport costs or satisfying Wardrop’s first principle of traffic equilibrium [1]
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