Public transportation systems are flexible and affordable for the passengers. In contrast, the operation and construction of the necessary infrastructure is cost-intensive and requires extensive planning. Decisions about the scheduling, capacities and the location of stations are dependent on various economic, social, and environmental factors and have a major impact on the structure of a city. In this context, information about the starting points and destinations of potential passengers is highly relevant for operators. Unfortunately, the collection of this data is not trivial and often based on time intensive and expensive studies.
In this project, we developed a novel approach to gain knowledge for transportation system optimization based on the data of taxi rides, which have been recorded for documentation purposes. This data can be analyzed and offers an insight into the fine-grained travel intentions of millions of people. The application enables the exploration of most frequent travel routes and can automatically suggest useful extensions of the exciting transportation system or suggest an optimized route map, which can be used to evaluate the existing one. With this functionality, the presented software effectively supports the decision processes of operators and enables the continuous evaluation of the existing systems.