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Social Cost Guarantees in Smart Route Guidance

机译:智能路线引导中的社会成本保证

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摘要

We model and study the problem of assigning traffic in an urban road network infrastructure. In our model, each driver submits their intended destination and is assigned a route to follow that minimizes the social cost (i.e., travel distance of all the drivers). We assume drivers are strategic and try to manipulate the system (i.e., misreport their intended destination and/or deviate from the assigned route) if they can reduce their travel distance by doing so. Such strategic behavior is highly undesirable as it can lead to an overall suboptimal traffic assignment and cause congestion. To alleviate this problem, we develop moneyless mechanisms that are resilient to manipulation by the agents and offer provable approximation guarantees on the social cost obtained by the solution. We then empirically test the mechanisms studied in the paper, showing that they can be effectively used in practice in order to compute manipulation resistant traffic allocations.
机译:我们对城市道路网络基础设施中的交通分配问题进行建模和研究。在我们的模型中,每个驾驶员都提交了他们的预期目的地,并分配了一条路线,该路线可将社会成本(即所有驾驶员的出行距离)降至最低。我们假设驾驶员具有战略意义,并尝试操纵系统(即错误报告其预定目的地和/或偏离指定路线),如果他们可以这样做可以减少行驶距离。这种战略行为是非常不希望的,因为它可能导致总体的次优交通分配并导致拥堵。为了缓解这个问题,我们开发了无现金机制,可以对代理商的操纵具有弹性,并为解决方案获得的社会成本提供可证明的近似保证。然后,我们对本文研究的机制进行经验测试,表明它们可以在实践中有效地用于计算抗操纵性流量分配。

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