Abstract: The post-disaster Advanced Traveler Information System(ATIS) can provide its users with traffic information in a timely manner, while non-ATIS users can only adjust their routes according to their own historical experience. In order to explore the road network resilience in a mixed scenario of two types of users, this paper introduces the dynamic time dimension into the resilience evaluation, constructs a mixed day-to-day dynamic flow distribution model of two types of users, proposes an ATIS information prediction method based on historical traffic, and designs a model solving algorithm. The simulation results show that, compared with the classical ATIS information prediction method, the average road network resilience supported by the proposed ATIS information prediction method increases by 2.48% in the research time domain.For the best road network resilience, the best ATIS market share is about 30%. When the market share of ATIS is 50%, 75% and 100%, the increase of ATIS information error improves the road network resilience value, while when the market share is 25%, the increase of ATIS information error reduces the road network resilience value.