High‐speed processing and high‐reliability technology in an integrated fixed‐line and wireless, autonomous decentralized IC card system

Abstract

SUMMARYIncreasing the processing speed of automatic fare collection gates (AFCG) is a topic of great importance for supporting passengers who are getting on and off high-density transportation at peak hours. On the other hand, reliability is indispensable for processing tickets, which are a type of noncurrency negotiable instrument. Therefore, a passenger ticket system that provides both high-speed processing and high reliability is required. To increase passenger convenience and reduce maintenance costs, a wireless IC card ticket system is desirable. However, since this system uses wireless communication for processing that is carried out with the fare collection gates, the drop in data during ticket examination is a problem. In this paper, the author proposes an autonomous decentralized technology for satisfying the requirements of high-speed processing and high reliability in a wireless IC card ticket system. IC cards, automatic fare collection gates, and a central server are designed as nodes of an autonomous decentralized system. In particular, to achieve high-speed processing, the author proposes an autonomous decentralized algorithm for fare calculation by IC cards and automatic fare collection gates. To prove the effectiveness of this algorithm, the author creates models and performs comparison tests. Also, as a technology for ensuring high reliability, the author proposes an autonomous decentralized data consistency technology for each subsystem. These technologies were introduced in the Suica system (East Japan Railway Company) in Japan and their effectiveness was proven.

Multi-layered Data Consistency Technology in Autonomous Decentralized IC Card Ticket System

“…That is, the best performance is realized with the appropriate parameters according to each system requirements. These conditions are made use of the practical "Suica" system at East Japan Railway Company and the system is running satisfactory, without any fatal errors [11].…”

“…Finally T exp , the expectation of the cumulative time for a datum to be adjusted, is delivered as (11) from (8) and (10). As in (11), T exp is a function of t j and j. With this function, the most appropriate number of layers and the most appropriate time for stay at each layer can be simulated.…”

Factors and Models for Promoting Consumer Use of Electronic Money

“…Our research procedure is as follows: (1) We develop a survey questionnaire on consumer awareness, intention, frequency of e-money usage, and current opportunities in the situations of transportation networks and shops in order to introduce e-money in corresponding regions. (2) We extract factors of consumer awareness of e-money from survey data through an exploratory factor analysis. (3) We develop two models that show the relationship between e-money use and the factors extracted in step 2 using SEM.…”

“…E-money is primarily used for transportation fare and retail shopping. The e-money infrastructure has provided numerous benefits as described later in detail [2,3]. E-money users electronically deposit monetary value to a smart card or a smartphone in exchange for cash.…”

“…When shopping with emoney, they can earn points. (2) The benefit for public transportation companies is 1/3 reduced maintenance costs of automatic ticket gates when compared to magnetic-type automatic ticket gates [6]. (3) Retailers can expect an increase in the number of customers due to reduced congestion and waiting times at cash registers, as well as reduced costs of maintaining and replacing cash registers, reduced handling costs of small change, and reduced risk of cash theft, and more.…”