Recently, with an increasing number of people traveling by car, there has been a growing demand for effective traffic management, reduced travel times, and improved road and street maintenance plans. Here, it is evident that drivers make a well-informed decision on which route to take by utilizing smartphone routing, traffic announcements, and advancements in navigation technology. In the present study, the authors aim to develop a road maintenance plan that incorporates a bi-level optimization and simulation framework. They focus on the upper level by optimizing the road maintenance plan; at a lower level, intelligent agents acting as savvy passengers seek to minimize driving time and wait times in traffic. To evaluate the intelligent behavior of agents in reducing travel time on blocked routes (due to road repairs) under various scenarios, the authors first calculate the agents’ behavior in finding the optimal travel demand route and then integrate the optimization of the road maintenance plan. The results of this study demonstrated the effectiveness of informing passenger agents and their intelligence in correcting routes and reducing travel time.