# Generating Activity-Based Mobility Plans from Trip-Based Models and Mobility Surveys
## 6 Conclusions  
This article presents an approach to reconstructing activity-based mobility plans from trip-based data and a general mobility survey. The presented approach was developed, implemented, and validated with the goal of generating artificial mobility plans that are realistic yet efficient to obtain. It is applicable to any geographically limited area with homogeneous mobility behavior, and it was tested and validated using a case study in the city of Munich. Based on a literature review on existing mobility models and the need for activity-based mobility plans in transportation engineering, this article identified a need for easy-to-implement mobility models capable of reproducing microscopically and macroscopically coherent mobility behaviors similar to activity-based models. While the capabilities of activity-based models with regard to the forecasting and explanation of mobility behavior are not needed for many applications, such as charging infrastructure simulations [52], their inherent complexities make them hard to implement and prevent them from being used pervasively. In contrast, the less complex trip-based or hybrid mobility models fail to model mobility behavior with the required microscopic accuracy. Hence, this article proposed a novel approach aimed at the reconstruction of status-quo mobility behavior from the output of trip-based models and general mobility surveys, with the general idea being that all information required to model mobility macroscopically and microscopically is conveyed by these two data sources and may be combined in a data-driven approach that is, for the most part, not reliant on any explicit behavioral modeling. While the resulting model does not offer the same forecasting and explanation potential as activity-based models and does not allow for any extrapolation of mobility behavior onto future scenarios, it is conceptually easier to implement and can be used in all cases in which the development of full-scale activity-based models is out of scope, but microscopic mobility modeling is needed. Within a case study conducted in the city of Munich, this approach proved to be both efficient and effective in creating activity-based mobility plans that were highly disaggregated yet did not fail to represent population-wide traffic indicators. The results obtained within the case study were based on data from MID and MITO, and they validated the suggested approach for the city of Munich, thus exemplifying that it is possible to generate realistic activity-based demands from trip-based models and general mobility survey data without adding the complexity of behavioral activity-based models. [PERSON] and Q.B. contributed equally to this work. [PERSON] conceived of the original idea to merge trip-based mobility plans with large-scale mobility survey data to generate activity-based mobility plans usable for mobility system simulation. Conceptualization, L.A. and Q.B. ; methodology, L.A. and Q.B. ; software, Q.B. ; validation, L.A. and Q.B. ; formal analysis, L.A. and Q.B. ; data curation, L.A. and Q.B. ; writing--original draft preparation, L.A. and Q.B. ; writing--review and editing, L.A. and Q.B. ; visualization, L.A. and Q.B. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the Technical University of Munich (TUM) in the framework of the Open Access Publishing Program. **Data Availability Statement:** Within this study two major input data sets have been used and described: general mobility data from the MID study and an output data set from the MITO model. Restrictions apply to the availability of both of these data sets. MID data was obtained from the \"DLR Clearing House Transport\" and are available upon request at [[https://daten.clearingstelle-verkehr.de/279/](https://daten.clearingstelle-verkehr.de/279/)]([https://daten.clearingstelle-verkehr.de/279/](https://daten.clearingstelle-verkehr.de/279/)) with the permission of \"DLR Clearing House Transport\".