Management of New Automatic Ticket Vending Machine System in Urban Rail Transit

• Published in: International journal of ambient computing and intelligence Vol. 15; no. 1; pp. 1 - 15
• Main Authors: Li, Yanshuo, Zhu, Hao, Tian, Weigang, Xiao, Chengshun
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 2024
• Subjects: Automatic fare collection; Automation; Big Data; Comparative analysis; Data analysis; Efficiency; Fares; International economic relations; Inventory; Light rail transit; Mobile commerce; Neural networks; Passengers; Peak hour traffic; Public transportation; Queuing theory; R&D; Research & development; Subways; Ticket sales; Traffic congestion; Urban rail; Vending machines; Vending machines industry; China
• ISSN: 1941-6237; 1941-6245
• DOI: 10.4018/IJACI.344796

The technology of automatic fare collection system for urban rail transit is an important technology for achieving automatic fare collection for public transportation facilities such as urban subways. This article studies the relevant characteristics of the AFC system. Through introducing queuing models, simulation comparative experiments, and neural network debugging, it is found that the automatic fare collection system for urban rail transit not only effectively helps station staff to allocate tickets in a timely and reasonable manner, adjust station ticket supply, but also facilitates station passengers to query tickets, and passengers can freely choose whether to take the train according to their actual needs. The experiment shows that the AFC system can effectively help passengers avoid traffic congestion during peak hours, greatly improve management level, and reduce labor intensity.