Analysis of a collaborative transport model mixing passengers with freights in metro system. (March 2023)

• Record Type: Journal Article
• Authors: Zuo, Tong; Li, Bozhi; Zhang, Fan; Yin, Yong
• Is Part Of: Journal of rail transport planning & management. Volume 25(2023)
• Publication Date: 2023-03
• Subjects: Urban logistics distribution -- Collaborative transportation -- Traffic congestion -- Metro system; Railroads -- Periodicals; Railroads -- Planning -- Periodicals; Railroads -- Management -- Periodicals; Railroads; Railroads -- Management; Railroads -- Planning; Periodicals; 385.068
• DOI: 10.1016/j.jrtpm.2022.100358
• Languages: English
• ISSNs: 2210-9706

Abstract

Abstract: Applying the surplus capacity of the metro system to carry out urban logistics distribution can efficiently ease traffic congestion and improve the efficiency of logistics distribution in an urban area. Taking the mode of setting up freight carriages at both ends of passenger trains as the research target, a collaborative transport model combining passengers and goods is developed to quantitatively analyze the actual performance of the logistics function in the metro system while making assumptions about uncertain factors. The method is implemented in a simulated analysis on the basis of the Chengdu metro network and current freight demand. Results show that the collaborative transport mode can meet 98.95% of the freight demand and alleviate 98.86% of the traffic congestion. Meanwhile, the average delivery time of collaborative transportation is 31.07 min, which is less than the 40.98 min delivery time of ground transportation, indicating that the former is more efficient. Moreover, the collaborative transportation model is more sensitive to changes in passenger flow than changes in freight demand. Therefore, separating the freight and passenger transport functions of the metro system will effectively reduce the impact of passenger flow changes on collaborative transportation. Highlights: A collaborative transport model mixing passengers and goods is established based on the metro system. The uncertain factors about time and cost that affect the freight transport processes are analyzed. The collaborative transport model is more sensitive to the change in passenger flow than freight demand. The model is of great significance to alleviate traffic congestion and improve the transport efficiency.