Investigating a tradable credit scheme with the system optimum theory. (May 2019)

• Record Type: Journal Article
• Authors: Lv, Jianyu; Zong, Fang; Tang, Ming; Yu, Ping
• Is Part Of: Advances in mechanical engineering. Volume 11:Number 5(2019)
• Publication Date: 2019-05
• Subjects: Big data -- tradable credit scheme -- system optimization -- traffic flow -- congestion pricing; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/1687814019851391
• Languages: English
• ISSNs: 1687-8132

Abstract

This article establishes a charging model for a tradable credit scheme based on the system optimum theory. The credit price and the distribution of the amount of tradable credit are determined with the model. The method of formulating the real-time tradable credit scheme in the circumstance of big data is also discussed. This article will enact the specific tradable credit scheme by adapting the charging model and then examine implementation effects after the scheme. The results indicate that the enacted tradable credit scheme by using the proposed charging model is helpful in reducing the total cost of the system and promoting the balance between traffic supply and demand. This suggests the effectiveness of the proposed tradable credit scheme and the feasibility of the charging model. A comparison between the tradable credit scheme and the congesting pricing strategy suggests the superior effect of the former strategy. The findings can be applied to formulating the tradable credit scheme, with which we can adjust travelers' path selection behaviors and promote the traffic flow to a balanced distribution status. This is benefit to the urban transportation system by alleviating the problem of traffic congestion, fuel consumption, and pollution emissions.