Urban freeway users’ diversion response to VMS that display travel time on both urban freeway and local streets was explored.Stated preference data of diversion behavior was used to develop a cross sectional binary probit model and a panel binary probit model for identifying factors that influence diversion response.Main findings regarding VMS impacts are travel time saving and drivers’ years of driving experience serve as positive factors in diverting;number of traffic lights on the local street,using frequency of urban freeway;being a mid age driver,and being an employer provided car driver serve as negative factors in diverting.On the modeling aspect,it was shown that the panel model does not provide substantially different model coefficients but more robust statistical inferences for model coefficients as compared to the cross sectional model,and the cross sectional model tends to seriously overestimate t test values for explanatory variables correlated with drivers (e.g.demographic characteristics) but slightly underestimate t-test values for explanatory variables correlated with scenarios (e.g.travel time savings).The findings have implications for better design and operation of advanced traveler information systems and for future effort on survey design,data collection and model estimation.