As a new solution to estimate OD-M of transport and to design tailored bus routes, the project B_us (commercial name of the project FitYourBus, funded by the European Commision H2020 programme frontierCities) proposes a new way of collecting and treating mobility pattern data in order to reduce about 36% the cost of data acquisition and 41% the cost of exploiting data, allowing the deployment of user-driven transport services. The proposed methodology includes the following stages: 1) Platform. Deployment of a back-end service and its administration interfaces. The data collection set-up is based on a client-server architecture using J2EE and Docker technologies; 2) Data collection. Users provide their basic commuting data –origin, destination, work hours, etc– using our cross-platform smartphone app, which communicates with the back-end service; 3) Data treatment. The collected data stored in a database is converted into a proper OD-M through an algorithm that combines Dijkstra's and A*algorithms, running as a MapReduce job on a Big Data Apache Hadoop engine. Single citizen objective optimization algorithm influences the development of the multi-objective optimization branches in the problem (maximizing the overall time savings for the participants at the same time as maximizes the number of passengers per bus). To test the methodology and validate the correct implementation of the algorithm, a pilot project has taken place in coordination with EMT, the main bus public company in the city of Madrid (Spain). The trial consisted in deploying employees’ bus routes to reach to and to go from one of their operation centres (involving about 1,300 workers, including drivers, mechanical technicians, and other workers). Mobility patterns data of 30.8% of them were obtained. After running the algorithm, the result was a set of vectors (one from each user), which was exported to a GIS platform to plot the first “draft corridors” surrounding the routes that go through the most repeated nodes. These corridors were particularized for the conditions of circulation of the buses and according to the schedules of the daytime and night-time of the rest of employees’ routes of EMT and the current public transport services in the metropolitan area. Results show that operation times of the two current employees’ routes have been reduced between 1.2% (but improving spatial coverage and frequencies) and 44.1% while has been increased the fleet utilization ratio because the service passes to be used by workers who previously did not use it (with a majority change from the car to the bus).