In this paper, we consider the problem of increasing efficiency of a transportation system through optimizing the behavior of commuters. The assumption is that the time spent in the traffic can be represented by a monetary value and hence introduction of monetary compensations can lead to a more efficient organization of the transportation system. In our model, heterogeneous travelers differently assess the value of their time spent in congestion, hence it is presumably viable to reduce traffic in the most congested streets by introducing a bidding mechanism that will allow the participants who have a lower monetary value of time to receive a compensation financed by the group of commuters that have a higher value of time spend in congestion. We start by presenting a design of a bidding system for optimal allocation of traffic. We analyze the properties of the proposed algorithm and show that it leads to a more efficient allocation of vehicles than the theoretical allocation that could be achieved in the Nash Equilibrium of an uncontrolled transportation network. Subsequently, we verify the proposed auction design via an agent-based simulation model representing the Manhattan area of New York City. The results of our simulation confirm theoretical findings that the introduction of the proposed auction mechanism in a real city settings leads to a more efficient allocation of routes or means of transportation chosen by commuters.

在本文中，我们考虑了通过优化通勤者的行为来提高运输系统效率的问题。假设交通中所花费的时间可以用货币值表示，因此引入货币补偿可以使运输系统更有效地组织起来。在我们的模型中，异类旅行者对拥堵时间花费的价值进行了不同的评估，因此，通过引入一种竞价机制，可以降低拥挤时间，从而降低交通拥堵时间，这是可行的。由在交通拥堵方面花费较高时间价值的通勤者群体提供的补偿。我们首先介绍一种出价系统的设计，以优化流量分配。我们分析了所提出算法的性质，并表明，与在不受控制的交通网络的纳什均衡中可以实现的理论分配相比，车辆分配效率更高。随后，我们通过代表纽约市曼哈顿地区的基于代理的仿真模型来验证提议的拍卖设计。我们的模拟结果证实了理论上的发现，即在实际城市环境中引入拟议的拍卖机制可导致通勤者选择的路线或交通工具的分配更加有效。我们通过代表纽约市曼哈顿地区的基于代理的仿真模型来验证提议的拍卖设计。我们的模拟结果证实了理论上的发现，即在实际城市环境中引入拟议的拍卖机制可导致通勤者选择的路线或交通工具的分配更加有效。我们通过代表纽约市曼哈顿地区的基于代理的仿真模型来验证提议的拍卖设计。我们的模拟结果证实了理论上的发现，即在实际城市环境中引入拟议的拍卖机制可导致通勤者选择的路线或交通工具的分配更加有效。