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Enhancing the Passenger Experience

with Proactive Travel Features

Intermodal trip planning, mobile ticketing, payment and real-time information updates along the way are integral parts of our mobility apps. Nevertheless, travelers have individual needs and preferences – whether they‘re alone or in a group.

With the new MyMobility feature, our trip planners become even more valuable companions: In learning from the users’ behavior and habits, the apps are able to deliver personalized and proactive mobility recommendations. Travelers’ preferences can be catered to without active input and future trip issues will be anticipated based on predictions. The individual traveler’s daily routines and events serve as a basis for real-time support and service tailored to specific needs.

MyMobility knows your daily travel routine

Take Laura as an example: She does not own a car and typically uses public transport or car sharing services to get to the university. When visiting her parents in the suburbs, she prefers to take the bus. The ticket price is more important to her than the number of transfers or the overall convenience of her trip. Thanks to MyMobility, her trip planner app acts as a proactive assistant on her way from A to B:  In case of disruptions on Laura’s usual tram line to university, she will automatically receive a push message suggesting an alternative route or an earlier departure in order to help her arrive on time. On the way to her parents, Laura will be reminded to buy an extension ticket before she leaves the travel zone her monthly pass is valid for. For Laura’s trip home, automatic route suggestions that take into account the real-time traffic situation, and recommendations based on weather conditions round out the service portfolio of MyMobility.

Data Sources for MyMobility

Explicit, implicit and contextual data help create reliable user profiles. The pool of explicit data is fed by information actively entered by the traveler or extracted from transactions and inputs from other smartphone apps. The user’s individual travel behavior, including commuter routes and preferred transit times, generates implicit data, whereas contextual data is derived from other sources and includes information on car sharing business areas, real-time traffic and weather.

Possible data sources for MyMobility include logs from existing HAFAS trip planner apps and mobile ticketing solutions, fleet management systems like HAFAS Smart VMS, the HAFAS Real-time Hub for information across transport modes, disruption messages from operating systems as well as external data sources for events, weather etc. – all of these can be flexibly defined.