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Equilibria and Inefficiency in Traffic Networks with Stochastic Capacity and Information Provision

机译:随机能力和信息规划的交通网络均衡和低效

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In this paper, we study the inefficiencies of various behavior equilibria in traffic networks with stochastic capacity and information provision. Variational inequality models are presented to formulate the travel behaviors associated with user equilibrium (UE) with imperfect information, system optimum (SO) with imperfect information and system optimum with perfect information, respectively. The tight upper bounds of inefficiencies caused by UE selfish behavior with imperfect information are analytically discussed in detail. It is found that when link travel time functions are all polynomial, the worst-case inefficiencies against the SOs with imperfect or perfect information are dependent upon the steepness degree of link time functions and independent of the network topology. The upper bound of inefficiency against the SO with perfect information is yet dependent upon the degradation degree and occurring probability density of link capacity. Furthermore, it is also found that perfect information can always improve the traffic network performance whilst imperfect information has the same worst-case efficiency as zero information.
机译:在本文中,我们研究了随机能力和信息提供的交通网络中各种行为均衡的低效率。提出了变形不等式模型以配制与用户平衡(UE)相关的旅行行为,其具有不完美信息的系统最佳(SO),分别与完美信息的最佳信息和系统最佳。详细讨论了由UE自私行为引起的无效引起的低效率的紧密上限。结果发现,当链路行进时间函数都是多项式时,具有不完美或完美信息的SOS的最坏情况低效率取决于链路时间函数的陡度和独立于网络拓扑。与完美信息的低效率的效率的上限尚未取决于链路容量的降解程度和发生的概率密度。此外,还发现,完美的信息始终可以提高业务网络性能,而不完美的信息具有与零信息相同的最坏情况效率。

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