11 Transportation Research Record: Journal of the Transportation Research Board, No. 2664, 2017, pp. 11–22. http://dx.doi.org/10.3141/2664-02 The dynamic multimodal network assignment problem at the daily schedule level is addressed by integrating an activity-based model and a dynamic traffic assignment tool through a unified framework. The framework achieves this integration while retaining disaggregated individualized information. The problem is formulated as a fixed-point problem, and equilibrium is achieved by minimizing the gap between the expected travel time, which is used by the activity-based model to generate the travelers’ individual and household activity schedules, and their experienced travel times, simulated by the dynamic traffic assignment tool. The schedule adjustment problem for individuals and households is formulated as a linear optimization problem. Two measures—inconsistent-schedule penalty and number of households with unrealistic schedules—are defined to monitor the status of the equilibrium and convergence gap of the integrated system. To ensure convergence of the applied integration, heuristic strategies for select- ing individuals for schedule adjustment and path swap are tested in a subarea network of Chicago, Illinois. Selecting individuals for sched- ule adjustment based on their inconsistent-schedule penalty reduces both defined measures significantly and leads to the convergence of the planned schedule and the experienced (i.e., simulated) schedule. Activity-based models (ABMs) and dynamic traffic assignment (DTA) procedures are advanced models on the demand and supply sides of transportation planning, respectively. Although they are conceptually and theoretically interrelated, in practice these models have developed along essentially independent tracks. Previous studies have sought to integrate the supply side with the demand side through various techniques, but few studies have addressed the equilibrium of users’ schedules within the context of ABM-DTA integration without losing disaggregated information. Simulation-based DTA tools allow modelers to incorporate disaggregate information into the estimates of travel costs that can be fed back into the ABM. This study presents a novel equilibrium state definition for the ABM-DTA integration framework and an algorithmic procedure to achieve it that takes into consideration individual schedule consistency between ABM and DTA as well as the usual equilibrium conditions in the multimodal transportation network. Furthermore, this study develops an approach for activity schedule consistency at the DTA level as part of an overall integration framework in order to improve the rate of convergence to the overall equilibrium state for the integrated model. Seeking consistency between the demand and supply sides in a traffic assignment model has long been a problem of interest for both research and practice. Early work in this area treats the demand and network performance as static; under these simplifying assumptions it is possible to obtain analytical solutions (1–4). However, deriving analytical solutions becomes challenging in advanced traffic assign- ment models that consider temporal dynamics and disaggregation of individuals, as in the DTA problem and therefore ABM-DTA integration (5–7 ). Hence, most DTA tools used in practice have adopted a simulation-based approach to capture the dynamics of flow propagation in networks (5, 6, 8–10). Notwithstanding the large body of work on modeling network dynamics on the one hand (6, 11–17 ) and activity-based models of travel demand on the other (18–23), much less work in the literature has addressed the integration of ABMs and DTA. Early efforts include recognition of the importance of modeling activity–trip chains at a disaggregate level in simulation-based network assignment proce- dures and incorporating activity rescheduling in the integrated model framework (24–26); a more recent theoretical contribution formulated the problem in an extended network representation (27 ). However, the main ABM-DTA challenges for actual applications include over- coming computational burdens and properly formulating and defin- ing the equilibrium state for the integrated system. Notwithstanding advances in computing, the former remains a significant concern for planning agencies, although perhaps less so for advanced research laboratories. The latter challenge is the principal focus of this study, along with algorithmic solution procedures and implementation tech- niques that also affect the computational aspects on large networks while preserving the integrity of the intended solution. Traditionally, integration schemes between the ABM and DTA involve aggregating the demand output, generated by the ABM, into time-dependent origin–destination matrices and feeding them into the DTA (28). Although this method is conceptually relatively straightfor- ward to implement, it loses the disaggregated individualized informa- tion, which is the major advantage of utilizing activity-based models in the first place. Recent studies focus on integrating ABM and DTA while minimizing information aggregation. Lu et al. describe the Schedule Consistency for Daily Activity Chains in Integrated Activity-Based Dynamic Multimodal Network Assignment Xiang (Alex) Xu, Ali Zockaie, Hani S. Mahmassani, Hooram Halat, Ömer Verbas, Michael Hyland, Peter Vovsha, and James Hicks X. Xu, H. S. Mahmassani, H. Halat, Ö. Verbas, and M. Hyland, Northwestern University Transportation Center, Northwestern University, 600 Foster Street, Evanston IL 60208. Current address for Ö. Verbas: Argonne National Labora- tory, 9700 South Cass Avenue, Argonne, IL 60439. A. Zockaie, Department of Civil and Environmental Engineering, Michigan State University, 428 South Shaw Lane, East Lansing, MI 48824. P. Vovsha, Parsons Brinckerhoff, One Penn Plaza, 250 West 34th Street, New York, NY 10119. J. Hicks, WSP USA (formerly Parsons Brinckerhoff ), 6100 Uptown Boulevard Northeast, Suite 700, Albuquerque, NM 87110. Corresponding author: H. S. Mahmassani, masmah@northwestern.edu.