We present behavioral models designed to capture the response of drivers to real-time traffic
information. In 2003, we have conducted a survey in Switzerland in order to collect both Revealed
Preferences (RP) and Stated Preferences (SP) about choice decisions in terms of route and mode. The RP
data contains socio-economic characteristics of the individuals in our samples, their actual usage of ITS as
well as their actual route and mode choice behavior. The SP data provide us with stated route and mode
choices when drivers are faced with different hypothetical choice situations involving real-time
information about the state of the network. First we present a Mixed Binary Logit model with panel data to
analyze the drivers’ decisions when traffic information is provided during their trip by the mean of Radio
Data System (RDS) or Variable Message Signs (VMS). This model is referred to en-route choice model.
Second we present Nested Logit models capturing the behavior of drivers when they are aware of traffic
conditions before their trip. These last models allow to predict pre-trip route choice decisions with regard
to route and mode when traffic information is available. The calibrated models are subsequently included
in a simulator which predicts travelers’ behavior in specific scenarios (described by adjustable parameters)
allowing the sensitivity analysis of the demand with regard to the variations of various parameters. In this
paper, we discuss the results of the estimation process, including some comments about the Value of
Travel Time Savings (VTTS) and present some scenarios developed with our simulator.
