This project aims to develop a transportation analytics solution that can be used by urban planners and public transit systems authorities. The solution is unique in that it is totally non-intrusive, i.e. does not require commuters’ opt-in, as well as being conveniently scalable. Our solution exploits cellular signal measurement reports to give some visibility and insights into commuters’ mobility patterns and transportation modes, e.g. walking, biking, scooter, bus, etc. Examples of questions that our solution should be able to answer include:
• How many means of transportation people use to get to work?
• How long do people need to walk when connecting between two modes of transportation?
• How long and painful is the “last mile” piece of the commuters’ journeys?
Investigator: