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Dynamic Traffic Equilibrium

Theoretical and Experimental Network Game Results in Single-Bottleneck Model
Authors: Gitakrishnan Ramadurai; Satish V. Ukkusuri;

Dynamic Traffic Equilibrium

Abstract

The existence of equilibrium solutions in single-bottleneck models with homogeneous travelers having the same preferred arrival times is explored from both theoretical and experimental frameworks. First, an equal payoff solution obtained in past studies is proved not to be in dynamic user equilibrium (DUE). Necessary conditions for DUE are presented, and the nonexistence of DUE in a single-bottleneck model with homogeneous commuters is proved. Second, a multiplayer online experimental network game that emulates the single-bottleneck model is discussed. The game is played online by real players and is repeated 21 times, each under no-information and online-information settings. The experimental setup and the results are described with insights from graphical plots and analysis. Specific emphasis is placed on the system's dynamic evolution in each game and the pattern of a user's decision making. It is anticipated that these results will provide important insight into the underlying behavioral decision making of travelers and will thereby facilitate the development of better dynamic traffic assignment models.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Average
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