Modeling Framework to Analyze Effect of Multiple Traffic Information Service Providers on Traffic Network Performance

Abstract

Along with the increasing popularity of mobile smart devices such as smartphones and tablet personal computers, traffic information is coming to drivers through many intelligent traffic applications. Many countries have multiple traffic information service providers (ISPs), who make every effort to improve their service quality to influence more people to subscribe to their services. Because such a commercial environment is developing, a study of the effect of multiple ISPs on road network performance is necessary. Therefore, a modeling framework of day-to-day dynamics in which multiple ISPs compete and cooperate with each other to enhance their subscriber service quality is developed in this study. A realistic information acquisition and learning mechanism that ensures consistent updating of individually perceived day-by-day travel times is incorporated for driver behavior in this framework. A bounded rational behavior model was adopted for route choice decisions. The framework is capable of investigating the effects of any potential competition or cooperation of multiple ISPs in the traffic information market in terms of their information-sharing strategies. Numerical experiments on a real network were conducted to analyze the impact of such interactions on the network performance. The results showed that a cooperative system was not necessarily the best for network performance and that there was an optimal level of market penetration of traffic information services in transportation networks beyond which the benefits no longer increased or even worsened.