  We propose a recursive logit model which captures the notion of choice
aversion by imposing a penalty term that accounts for the dimension of the
choice set at each node of the transportation network. We make three
contributions. First, we show that our model overcomes the correlation problem
between routes, a common pitfall of traditional logit models, and that the
choice aversion model can be seen as an alternative to these models. 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 may
decrease the probability for existing paths. Finally, we show that under the
presence of choice aversion, adding edges to the network can make users worse
off. In other words, a type of Braess's paradox can emerge outside of
congestion and can be characterized in terms of a parameter that measures
users' degree of choice aversion. We validate these contributions by estimating
this parameter over GPS traffic data captured on a real-world transportation
network.
