Abstract This study establishes Markovian traffic equilibrium assignment based on the network generalized extreme value (NGEV) model, which we call NGEV equilibrium assignment. The use of the NGEV model for route choice modeling has recently been proposed, and it enables capturing the path correlation without explicit path enumeration. However, the theoretical properties of the model in traffic assignment have yet to be investigated in the literature, which has limited the practical applicability of the NGEV model in the traffic assignment field. This study addresses the research gap by providing the theoretical developments necessary for the NGEV equilibrium assignment. We first show that the NGEV assignment can be formulated and solved under the same path algebra as the traditional Markovian traffic assignment models. Moreover, we present the equivalent optimization formulations to the NGEV equilibrium assignment. The formulations allow us to derive both primal and dual types of efficient solution algorithms. In particular, the dual algorithm is based on the accelerated gradient method that is for the first time applied in the traffic assignment. The numerical experiments showed the excellent convergence and complementary relationship of the proposed primal and dual algorithms.
Highlights Markovian traffic equilibrium assignment based on the network generalized extreme value model is established. Path algebra that generalizes the Markovian traffic assignment models is presented. Primal and dual optimization problems to the equilibrium assignment are provided. Efficient solution algorithms based on the partial linearization and accelerated gradient methods are proposed. Complementary relationship between the primal and dual types of algorithms is shown through numerical experiments.
Markovian traffic equilibrium assignment based on network generalized extreme value model
Transportation Research Part B: Methodological ; 155 ; 135-159
2021-10-15
25 pages
Article (Journal)
Electronic Resource
English
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