From Mobile Phone Data to Transport Network -- Gaining Insight about Human Mobility

In this paper we present methods for mapping trajectories of cell tower latitude-longitudes in mobile phone data to transport network. Compared to other forms of mobile phone data such as GPS traces, this form is the most popular and inexpensive but the least accurate and highly irregular. Unlike some earlier works on this type of data where only long trips are studied, our work is based on everyday transportation inside a city. The problems due to inaccuracy in determining position of a user and irregularity of phone events are felt even more intensely for such small distances. Our approach in processing this data takes into account its repetitive nature, i.e., A typical user makes the same trips every week. Moreover, many users follow the same transport route to go from one place to another. First of all, we defined stay region taking into consideration irregularity of phone events. Then we extracted trajectories between each pair of stay regions as trips. Then, we map these trips to existing transportation network consisting of bus services, train lines, expressways, and their combinations such as bus-train-bus. For a given origin and destination, we create a heat map that shows the most commonly used route. A round-the-clock heat map, both for weekdays and weekends, shows people's mobility at different times of a week. We validate our findings by both direct (sample survey) and indirect (comparison with available statistics) methods.