Ordered probit model for the frequency of usage of GPS-based ATIS system in New York’s Capital District

 

Ordered probit model for the frequency of usage of GPS-based ATIS system in New York’s Capital District

Sage 4101

Traffic congestion is a very common problem that affects people around the world. Intelligent Transportation Systems are a feasible and convenient solution to reduce traffic congestion and optimize the utilization of resources. Advance Traveler Information Systems (ATIS) constitute an important element to intelligent Transportation Systems (ITS) that is relatively inexpensive and with a low environmental impact. An ATIS system is composed of in-vehicle information and guidance systems to support the driver’s route selection when trying to avoid traffic congestion. The success of an ATIS system is not only dependable of the quality of the information given to the driver; it also depends on the decision of the driver in respect to re-routing. Hence it is important to understand the factors affecting the driver’s decision making processes of route choice when traffic information is provided. The main objective of this research is to develop a mathematical model to understand and predict the frequency with which the drivers will follow the route advice provided by the ATIS system. The model describes the usage of GPS-based ATIS devices in the morning commute of drivers in New York’s Capital District region. The term usage is used to describe the frequency in which the drivers decide to follow the route advice provided by the GPS-based ATIS device. As part of a field experiment with a GPS-based ATIS system the participants were administered with a pre and post experiment surveys. The data obtained in both surveys was used for the development of the proposed model. Given the ordered nature of the dependent variable the ordered probit modeling approach was selected as the best alternative to construct the model. It will be demonstrated that both socio-economic and commute characteristics had an influence in the individual decisions of the drivers regarding route selection when they receive traffic information.
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