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

机译:具有随机容量和信息提供的交通网络的平衡与效率低下

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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,我们研究了具有随机容量和信息提供的交通网络中各种行为均衡的效率低下。提出了变分不等式模型,分别用与不完全信息的用户平衡(UE),不完全信息的系统最优(SO)和具有完美信息的系统最优来描述出行行为。详细分析了由具有不完善信息的UE自私行为导致的效率低下的严格上限。发现当链路旅行时间函数都是多项式时,针对具有不完善或完美信息的SO的最坏情况的效率低下取决于链路时间函数的陡度并且与网络拓扑无关。具有完美信息的SO的低效率上限仍然取决于链路容量的降低程度和出现的概率密度。此外,还发现,完美的信息始终可以改善交通网络的性能,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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