Modeling Travelers' Responses to Incident Information Provided by Variable Message Signs in Calgary, Canada

Abstract

This paper presents an investigation of drivers' response behaviors to intelligent transportation systems. It describes the results of a detailed survey and the results of an econometric model of route diversion behavior in response to real-time information provided by variable message signs (VMSs). The study location was Deerfoot Trail in Calgary, Canada. In case of major delays because of accidents on Deerfoot Trail, the City of Calgary uses 12 VMSs along Deerfoot Trail to divert drivers to alternative parallel arterials. A survey of 500 Deerfoot Trail commuters was conducted to examine the factors affecting drivers' compliance with VMSs. A latent discrete choice model was developed to model the responses of drivers to VMSs. This model introduces behavioral variables within a discrete choice model by endogenously estimating the latent variables. The primary finding of the study is that the en route information provided by VMSs convinces few drivers to change their trip destinations. Of the 500 respondents, 63.3% of drivers alter their trip plans in light of the information provided. However, 36.7% of drivers experience inertia by not altering their route, despite the excessive delays because of route blockage. The empirical model shows that driving experience, familiarity with alternative routes, trip purpose, trip time, trip length, and complementary information sources (e.g., the radio) are the most important factors influencing route-switching behavior in response to VMSs. In addition, drivers' attitudes toward VMSs were found to have the most significant impact on their responses to these systems.