scholarly journals Investigating the Impacts of Transaction Cost under a Tradable Credit Scheme with Heterogenous Users

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Fang Zhang ◽  
Jian Lu ◽  
Xiaojian Hu ◽  
Tenghui Liu
Keyword(s):  
Transaction Cost ◽  
Network Flow ◽  
Trading Volume ◽  
User Equilibrium ◽  
Trading Market ◽  
Tradable Credit Scheme ◽  
Trial And Error Method ◽  
Tradable Credit ◽  
Specific Number ◽  
Error Method

In this paper, the impacts of transaction cost are investigated under a tradable credit scheme (TCS) considering user heterogeneity. Under the credit scheme, a certain number of credits are initially distributed among all the travelers for a specific O-D pair, and a link-specific number of credits are charged from travelers using that link. The scheme allows for free trading of the credits among travelers, and both the sellers and buyers need to pay an extra transaction cost, which is associated with trading volume. Travelers in the network are assumed to be heterogenous with a discrete value of time (VOT). For a given tradable credit scheme and discrete VOT set, the combined network user equilibrium (UE) and credit-trading market equilibrium (ME) are formulated as a variational inequality (VI) problem, and the conditions for the uniqueness of the network flow pattern and the credit price at equilibrium are established. A bisection-based trial-and-error method is proposed to solve the proposed VI problems. Based on the simulation results, the computational advantages of the proposed method are demonstrated. Then, an example network is presented to investigate the effect of transaction cost in different kinds of markets. It is found that the implementation of transaction cost can suppress trading volume and either elevate or drive down the equilibrium credit price. Besides, it is also found that users with the lowest VOT suffer the most from the increase in transaction cost, while those with the higher VOT are more likely to experience a reduction in travel cost with the implementation of TCS.

scholarly journals Trial and error method for optimal tradable credit schemes: The network case

2013 ◽  
Vol 48 (6) ◽  
pp. 685-700 ◽  
Author(s):  
Xiaolei Wang ◽  
Hai Yang ◽  
Deren Han ◽  
Wei Liu
Keyword(s):  
Trial And Error ◽  
Trial And Error Method ◽  
Tradable Credit ◽  
Error Method

scholarly journals Traffic Equilibrium for Mixed Traffic Flows of Human-Driven Vehicles and Connected and Autonomous Vehicles in Transportation Networks under Tradable Credit Scheme

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Fang Zhang ◽  
Jian Lu ◽  
Xiaojian Hu
Keyword(s):  
Autonomous Vehicles ◽  
Network Performance ◽  
Penetration Rate ◽  
User Equilibrium ◽  
Unit Price ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Stochastic User Equilibrium ◽  
Tradable Credit Scheme ◽  
Tradable Credit

In this paper, the traffic equilibriums for mixed traffic flows of human-driven vehicles (HDV) and connected and autonomous vehicles (CAV) under a tradable credit scheme (TCS) are established and formulated as two variational inequality (VI) problems with exogenous and endogenous CAV penetration rate, respectively. A modified Lagrangian dual (MLD) method embedded with a revised Smith’s route-swapping (RSRS) algorithm is proposed to solve the problems. Based on the numerical analysis, the impacts of CAV penetration and the extra expense of using a CAV on network performance are investigated. A novel driveway management, autonomous vehicle/credit charge (AVCC) link, is put forward to improve the efficiency of TCS. Under the TCS with exogenous CAV penetration rate, a logit-based model is applied to describe the stochastic user equilibrium for mixed traffic flow. It is found that the penetration of CAV gives rise to a better network performance and it can be further improved by the deployment of AVCC link. Under the TCS with endogenous penetration rate, a nested-logit model is applied to describe travelers’ choices of vehicle types and routes. It is found that the deployment of AVCC links can slow down the decline rate of CAV penetration with increasing expense and thus ensure a lower average travel time for CAVs. In both cases, the deployment of AVCC links can stimulate credit trading and drop down its unit price.

scholarly journals A Trial-and-Error Method with Autonomous Vehicle-to-Infrastructure Traffic Counts for Cordon-Based Congestion Pricing

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Zhiyuan Liu ◽  
Yong Zhang ◽  
Shuaian Wang ◽  
Zhibin Li
Keyword(s):  
Autonomous Vehicle ◽  
User Equilibrium ◽  
Trial And Error ◽  
Stochastic User Equilibrium ◽  
Traffic Counts ◽  
Vehicle To Infrastructure ◽  
Asymmetric Link ◽  
Trial And Error Method ◽  
Link Travel Time ◽  
Error Method

This study proposes a practical trial-and-error method to solve the optimal toll design problem of cordon-based pricing, where only the traffic counts autonomously collected on the entry links of the pricing cordon are needed. With the fast development and adoption of vehicle-to-infrastructure (V2I) facilities, it is very convenient to autonomously collect these data. Two practical properties of the cordon-based pricing are further considered in this article: the toll charge on each entry of one pricing cordon is identical; the total inbound flow to one cordon should be restricted in order to maintain the traffic conditions within the cordon area. Then, the stochastic user equilibrium (SUE) with asymmetric link travel time functions is used to assess each feasible toll pattern. Based on a variational inequality (VI) model for the optimal toll pattern, this study proposes a theoretically convergent trial-and-error method for the addressed problem, where only traffic counts data are needed. Finally, the proposed method is verified based on a numerical network example.

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