Effects of Information Heterogeneity in Bayesian Congestion Games
Jeff Liu, Galina A. Schwartz, Saurabh Amin

Citation
Jeff Liu, Galina A. Schwartz, Saurabh Amin. "Effects of Information Heterogeneity in Bayesian Congestion Games". Transportation Science (submitted for review), 2016; This article is currently under review. .

Abstract
This article studies the value of information in route choice decisions when a fraction of players have access to high accuracy information about traffic incidents relative to others. To model such environments, we introduce a Bayesian congestion game, in which players have private information about incidents, and each player chooses her route on a network of parallel links. The links are prone to incidents that occur with an ex-ante known probability. The demand is comprised of two player populations: one with access to high accuracy incident information and another with low accuracy information, i.e. the populations differ only by their access to information. The common knowledge includes: (i) the demand and route cost functions, (ii) the fraction of highly-informed players, (iii) the incident probability, and (iv) the marginal type distributions induced by the information structure of the game. We present a full characterization of the Bayesian Wardrop Equilibrium of this game under the assumption that low information players receive no additional information beyond common knowledge. We also compute the cost to individual players and the social cost as a function of the fraction of highly-informed players when they receive perfectly accurate information. Our first result suggests that below a certain threshold of highly-informed players, both populations experience a reduction in individual cost, with the highly-informed players receiving a greater reduction. However, above this threshold, both populations realize the same equilibrium cost. Secondly, there exists another (lower or equal) threshold above which a further increase in the fraction of highly-informed players does not reduce the expected social costs. Thus, once a sufficiently large number of players are highly informed, wider distribution of more accurate information is ineffective at best, and otherwise socially harmful.

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Citation formats  
  • HTML
    Jeff Liu, Galina A. Schwartz, Saurabh Amin. <a
    href="http://www.cps-forces.org/pubs/128.html"
    >Effects of Information Heterogeneity in Bayesian
    Congestion Games</a>, <i>Transportation Science
    (submitted for review)</i>,  2016; This article is
    currently under review. .
  • Plain text
    Jeff Liu, Galina A. Schwartz, Saurabh Amin. "Effects of
    Information Heterogeneity in Bayesian Congestion
    Games". <i>Transportation Science (submitted for
    review)</i>,  2016; This article is currently under
    review. .
  • BibTeX
    @article{LiuSchwartzAmin16_EffectsOfInformationHeterogeneityInBayesianCongestion,
        author = {Jeff Liu and Galina A. Schwartz and Saurabh Amin},
        title = {Effects of Information Heterogeneity in Bayesian
                  Congestion Games},
        journal = {Transportation Science (submitted for review)},
        year = {2016},
        note = {This article is currently under review. },
        abstract = {This article studies the value of information in
                  route choice decisions when a fraction of players
                  have access to high accuracy information about
                  traffic incidents relative to others. To model
                  such environments, we introduce a Bayesian
                  congestion game, in which players have private
                  information about incidents, and each player
                  chooses her route on a network of parallel links.
                  The links are prone to incidents that occur with
                  an ex-ante known probability. The demand is
                  comprised of two player populations: one with
                  access to high accuracy incident information and
                  another with low accuracy information, i.e. the
                  populations differ only by their access to
                  information. The common knowledge includes: (i)
                  the demand and route cost functions, (ii) the
                  fraction of highly-informed players, (iii) the
                  incident probability, and (iv) the marginal type
                  distributions induced by the information structure
                  of the game. We present a full characterization of
                  the Bayesian Wardrop Equilibrium of this game
                  under the assumption that low information players
                  receive no additional information beyond common
                  knowledge. We also compute the cost to individual
                  players and the social cost as a function of the
                  fraction of highly-informed players when they
                  receive perfectly accurate information. Our first
                  result suggests that below a certain threshold of
                  highly-informed players, both populations
                  experience a reduction in individual cost, with
                  the highly-informed players receiving a greater
                  reduction. However, above this threshold, both
                  populations realize the same equilibrium cost.
                  Secondly, there exists another (lower or equal)
                  threshold above which a further increase in the
                  fraction of highly-informed players does not
                  reduce the expected social costs. Thus, once a
                  sufficiently large number of players are highly
                  informed, wider distribution of more accurate
                  information is ineffective at best, and otherwise
                  socially harmful.},
        URL = {http://cps-forces.org/pubs/128.html}
    }
    

Posted by Saurabh Amin on 15 Apr 2016.
Groups: forces
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