Optimization of Individual Travel Behavior through Customized Mobility Services and their Effects on Travel Demand and Transportation Systems

In recent years a lot of new mobility services (e.g. multi- or intermodal travel management and information systems) came up. Today, users have to choose between a high variety of different mobility services and options. To reduce the complexity of these services, customized solutions to support the users are needed. Therefore, we present the development of a mobility assistance system. The assistance gathers information from timetables and real time information systems in public transportation, is connected to mobility services like car sharing, knows the users schedule and only presents relevant information for the ongoing situation. It supports the user's travel behavior by providing information on mode, route or alternative starting times of trips. According to the user's preferences, the assistance may adapt and reorganize the user's weekly activity schedule. To evaluate the impact on travel behavior caused by the mobility assistance, we use the travel demand model mobiTopp. We develop a new module in the model to generate activity patterns. That enables us to get more insights into travel behavior and to evaluate the changes occurred by the usage of the mobility assistance on personal level (e.g. how does the number of trips change) as well as on network level (e.g. how does the morning peak shifts when a certain amount of people is using the assistance).