# Generating Activity-Based Mobility Plans from Trip-Based Models and Mobility Surveys
## 2 The Related Literature and Problem Statement
### Problem Statement  
While activity-based models achieve remarkably realistic levels in modeling human behavior in theory, the inherent complexity and implementation efforts simultaneously restrict them from widespread use in practice. As a result, there is a gap between the state-of-the-art research and general application [5; 51]. In conclusion, the implementation efforts of activity-based models still outweigh the limitations of trip-based models in the eyes of many potential users, such as transportation researchers, city planners, and governmental authorities. Hybrid models such as the one presented by [PERSON] et al. [5] opt to reduce the gap between trip-based and activity-based models while simultaneously retaining the induced implementation efforts at a manageable level. Nevertheless, existing hybrid models do not reproduce microscopically accurate results. As a result, mobility plans generated by these approaches may include virtual agents who are located in two places at once or conduct activities in unreasonable frequencies or orders. In addition to hybrid approaches, the gap between the trip-based macrosimulations and activity-based microsimulations of human behavior also houses the potential for a second intermediary research domain that microscopically reconstructs mobility on a personal, vehicular, or household level for a singular scenario with regard to time and space. This domain differs from activity-based models by not modeling the behavior required to, for example, simulate the traffic response to policy changes such as congestion charges but still reproduce the existing mobility of individual entities in a consistent and realistic way while simultaneously retaining realistic macroscopic transport indicators. Compared with activity-based models, this significantly reduces the effort of applying the model while, at the same time, providing the same value to applications that need a realistic microscopic model of today's traffic but do not require to model's behavioral responses at all. This work presents an approach to filling the outlined gap by building a model on two different input data sets: an existing trip-based model reflecting accurate mobility behavior for the target region with regard to the macroscopic indicators and spatial resolution and a general mobility survey comprising information on the typical activity patterns of people representative of the population of the same target region. Utilizing these data sets as well as existing partial mobility models on, for example, driving and detour willingness, the presented approach fills the outlined research gap. One possible application, forming the motivation for the contribution presented in this article, is the simulation of urban electromobility using a simulation framework presented by [PERSON] and [PERSON] [52]. In this application, microscopically realistic mobility plans of individual battery electric vehicles are required to consistently simulate their state of charge and induced charging behavior. The respective approach is based on the hypothesis that future electric vehicle users behave exactly as today's drivers of internal combustion engine vehicles do with respect to mobility behavior. To this end, the overall amount, length, and spatial distribution of car trips needs to be remodeled based on the status quo for the target region in order to evaluate the spatiotemporal infrastructure utilization in the future. Although real transport demand is known to be elastic and hence sensitive to, for example, price changes [53; 54; 55] which inevitably come with the switch to another propulsion technology, a ceteris paribus analysis of charging behavior helps to reveal the general influences of technological changes and serves to reduce the system complexity to a manageable level. In these kinds of circumstances, activity-based models are out of scope and trip-based, and existing hybrid models are also not applicable because the traceability of individual cars is not provided.