A Recursive Logit Model with Choice Aversion and Its Application to Route Choice Analysis
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We introduce a route choice model that incorporates the notion of choice aversion in transportation networks. Formally, we propose a recursive logit model which incorporates a penalty term that accounts for the dimension of the choice set at each node of the network. We make three contributions. First, we show that our model overcomes the correlation problem between routes, a common pitfall of traditional logit models. In particular, our approach can be seen as an alternative to the class of models known as Path Size Logit (PSL). Second, we show how our model can generate violations of regularity in the path choice probabilities. In particular, we show that removing edges in the network can decrease the probability of some existing paths. Finally, we show that under the presence of choice aversion, adding edges to the network can increase the total cost of the system. In other words, a type of Braess's paradox can emerge even in the case of uncongested networks. We show that these phenomena can be characterized in terms of a parameter that measures users' degree of choice aversion.
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