This paper develops a method suitable for analyzing en route diversion behavior, with a corresponding probit model to analyze and quantify the impact of the content of different variable message signs (VMSs) and other factors on traffic diversion, based on real-time traffic data in Shanghai, China. The results were compared with a probit model based on a stated preference (SP) survey. To minimize the impact of varying origin–destination demand and travelers’ route selection behavior, this method seeks to study the impact of VMSs during a short period before and after a message switch, and uses relative diversion–compliance indices to evaluate the impact of information changes and absolute diversion–compliance indices quantitatively to analyze the impact of VMS messages on drivers’ en route behavior. Many results are consistent with the SP survey. Time factors, off-ramp conditions, and visibility of downstream congestion significantly influence en route behavior; this influence can explain the significant difference between the result from an en route model based on an SP survey and the real traffic system.
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