Automated Vehicle Identification (AVI) data has been prevalent in China due to high coverage of policy camera. Longitudinal AVI data has the potential to help interpret commuters’ route choice behavior and further help to build a Dynamic Traffic Assignment (DTA) model of large-scale road networks. With the help of DTA model, we can understand the influence of the evolution of route choice preference on traffic operation efficiency. In this study, we adopted the finest AVI dataset so far in Shanghai, China and performed route choice preference classification. With AVI trajectories and multi-source traffic data, a DynusT DTA model was built and calibrated from the both sides of supply and demand. Then we investigated the impact of route choice preferences. It is found that if all commuters followed suggestions of user equilibrium route choice, the total travel time across the entire network would be saved by around 35%, which is significant.
 

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