A Recursive Logit Model with Choice Aversion and Its Application to Transportation Networks

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Tác giả: Austin Knies, Jorge Lorca, Emerson Melo

Ngôn ngữ: eng

Ký hiệu phân loại: 003.56 Decision theory

Thông tin xuất bản: 2020

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 165316

 Comment: 58 pages, 12 figures, 6 tables
  forthcoming at Transportation Research Part B: MethodologicalWe 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.
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