Integrated Deployment Architecture for Predictive Real-Time Traffic Routing Incorporating Human Factors Considerations

As Advanced Traveler Information Systems (ATIS) are being more widely accessed by drivers, understanding drivers’ behavioral responses to real-time travel information through ATIS and its consequential benefits are important to the widespread deployment of ATIS technologies. Traditionally, the benefits of real-time travel information have been explored in two dimensions: (i) improving personal travel experience by reducing travel time and its uncertainty in drivers’ decision-making, and (ii) enhancing the performance of the entire traffic network by motivating drivers to use less congested routes. However, despite the strengthened effectiveness of real-time travel information with the recent increased deployment of ATIS through various sources, the increasing amount of information from multiple sources may cause extra stresses in perception of the information in relation to drivers’ cognitive ability and the particular travel context. In addition, the psychological benefits from the information in relation to the better knowledge or reassured feeling have not been addressed in the literature. In this context, this study proposes an analytical framework to understand the comprehensive benefits of real-time travel information with consideration of the qualitative and cognitive limitations in the processing procedure. Human factor issues play a critical role in the framework, especially when multiple and heterogeneous sources of information exist. The proposed framework from the psychological aspect allows systematic analysis of the benefits of real-time information that include conventional values such as travel time savings as well as the qualitative and psychological attributes that affect behavioral responses to the real-time information.