2009
DOI: 10.1007/s12205-009-0117-5
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Effects of user equilibrium assumptions on network traffic pattern

Abstract: The user equilibrium concept in traffic assignment is based on fundamental assumptions: perfect information, rationality, and homogeneity. This study examines changes in the traffic pattern and the network behavior when these assumptions are relaxed. In order to relax these assumptions, we employ a day-to-day evolution approach and develop agent-based simulation models that include drivers' learning model, preference model and preference sensitivity. Using the developed models, we investigate how each assumpti… Show more

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Cited by 23 publications
(13 citation statements)
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“…With FIFO violation function, the choice probability equilibrium was also found with the minimization of FIFO violation. The equilibrium within a perception boundary can be interpreted as the user optimal choice with bounded rationality which is frequently used in route choice problems (Nakayama et al, 1999;Kim et al, 2009). It can be interpreted a local equilibrium and more relaxed behavior assumption than a user equilibrium principle.…”
Section: Discussionmentioning
confidence: 99%
“…With FIFO violation function, the choice probability equilibrium was also found with the minimization of FIFO violation. The equilibrium within a perception boundary can be interpreted as the user optimal choice with bounded rationality which is frequently used in route choice problems (Nakayama et al, 1999;Kim et al, 2009). It can be interpreted a local equilibrium and more relaxed behavior assumption than a user equilibrium principle.…”
Section: Discussionmentioning
confidence: 99%
“…For example, Chorus and Dellaert [15] thought that the wish to save cognitive resources could lead travelers to inertial choices; Site and Filippi [27] explained that phenomenon in terms of "loss aversion"-the disadvantages of a move from the status quo are valued more heavily than the advantages. Besides saving cognition and avoiding loss aversion, other behavioral mechanisms which generate inertial behavior include the asymmetric preference [4,22], prevailing choice set [28], habitual behavior [29,30], familiarity, prior decision [21], risk aversion [31], endowment effect [32], and so on.…”
Section: Introductionmentioning
confidence: 99%
“…A model system of drivers' cognition, learning, and route choice was formulated to determine the dynamic characteristics of a driver-network system through microsimulation. Kim et al [2] used a day-to-day evolution approach and developed agent-based simulation models to investigate how three assumptions of the user equilibrium (UE) principle (perfect information, rationality, and homogeneity) influence network traffic flows. Wei et al [3] proposed a day-today route choice model based on reinforcement learning to analyze the effects of traveler's memory, learning rate, and experience cognition on the evolution of traffic flow using multiagent simulation.…”
Section: Introductionmentioning
confidence: 99%