Personalized Pareto-improving pricing-and-routing schemes for near-optimum freight routing: An alternative approach to congestion pricing
Personalized Pareto-improving pricing-and-routing schemes for near-optimum freight routing: An alternative approach to congestion pricing
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DOI：
10.1016/j.trc.2021.103004
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发表时间：
2021-02-26
影响因子：
8.3
通讯作者：
Ioannou, Petros A.
中科院分区：
文献类型：
--
作者：
Papadopoulos, Aristotelis-Angelos;Kordonis, Ioannis;Ioannou, Petros A.
交通拥挤是城市地区的一个主要问题。卡车由于体积大、动力慢和油耗高，造成拥堵，并对环境产生负面影响。卡车司机的个人路线决策不会导致系统的最佳操作，并有助于交通不平衡，特别是在卡车数量相对较高的地方。在本文中，我们设计了一个协调机制的卡车司机，使用定价和路由计划，可以帮助缓解交通拥堵的一般运输网络。我们考虑用户的异质性价值的时间（VOT），采用多类模型与随机起源？目的地（OD）对卡车司机的要求。该机制的主要特征是协调器要求卡车司机声明他们期望的OD对并从N个可用选项的集合中挑选他们的个体VOT，并且保证所得到的定价和路由方案是帕累托改进的，即，与用户均衡（UE）相比，每个卡车司机都将更好，并且每个卡车司机都将有动机如实地声明他/她的VOT，同时导致平均收入中性（预算平衡）机制。这种方法使我们能够设计个性化的（基于VOT）pricingand-routing方案。我们证明了最优定价方案（OPS）可以通过求解一个非凸优化问题来计算。为了提高计算效率，我们提出了一个近似最优定价方案（AOPS），并证明它满足上述性质。这两个定价和路由计划相比，拥挤定价与统一的收入退还（CPURR）计划通过广泛的仿真实验，它表明，OPS和AOPS实现了更低的预期总旅行时间和预期总货币成本的用户相比，CPURR计划，而不会产生负面影响的网络的其余部分。这些结果证明了个性化（基于VOT）定价的效率，
Traffic congestion constitutes a major problem in urban areas. Trucks contribute to congestion and have a negative impact on the environment due to their size, slower dynamics and higher fuel consumption. The individual routing decisions made by truck drivers do not lead to system optimum operations and contribute to traffic imbalances especially in places where the volume of trucks is relatively high. In this paper, we design a coordination mechanism for truck drivers that uses pricing-and-routing schemes that can help alleviate traffic congestion in a general transportation network. We consider the user heterogeneity in Value-Of-Time (VOT) by adopting a multi-class model with stochastic Origin?Destination (OD) demands for the truck drivers. The main characteristic of the mechanism is that the coordinator asks the truck drivers to declare their desired OD pair and pick their individual VOT from a set of N available options, and guarantees that the resulting pricing-and-routing scheme is Pareto-improving, i.e. every truck driver will be better-off compared to the User Equilibrium (UE) and that every truck driver will have an incentive to truthfully declare his/her VOT, while leading to a revenue-neutral (budget balanced) on average mechanism. This approach enables us to design personalized (VOT-based) pricingand-routing schemes. We show that the Optimum Pricing Scheme (OPS) can be calculated by solving a nonconvex optimization problem. To improve computational efficiency, we propose an Approximately Optimum Pricing Scheme (AOPS) and prove that it satisfies the aforementioned properties. Both pricing-and-routing schemes are compared to the Congestion Pricing with Uniform Revenue Refunding (CPURR) scheme through extensive simulation experiments where it is shown that OPS and AOPS achieve a much lower expected total travel time and expected total monetary cost for the users compared to the CPURR scheme, without negatively affecting the rest of the network. These results demonstrate the efficiency of personalized (VOT-based) pricing-and