In the past few days we came to the following insight:
„How might we use live data from the destination to select the best route?“
The service is based on an app that integrates data given by users with live-data on route and destination (like scanning free parking spots) to determine the most efficient means of traveling based on the customer‘s preferences and the enviromental conditions.
For this to work, the customer needs to provide information on which services he is already registered with. Based on the users needs like cost and time efficiency, comfort etc. the system suggests a route and possibly a combination of different services. It will guide the user to a parking spot and inform possible connecting services. For instance the system might suggest the use of a taxi, if no parking spots are available at the destination, combined with car sharing to reduce the overall cost of the trip. This use case is also illustrated in a video:
This service allows the user to save time and money. He can scale his preferences and the app might even suggest services the user was not previously aware of. Most importantly, it will take the hassle out of inner city travel. Especially the search for parking spots can be very stressful.
As mentioned, our system requires live data on traffic and available parking spaces. Means to gather such data are currently being researched by various institutions. If our servcie where to become real we have to collaborate with these entities as well as consolidate input of various data sources and of develop the actual algorithms. Further improvements to the service could also involve parking spot reservation.