Mobile call data records could provide the Big Data urban transport planning badly needs
If India is to have 100 smart cities, it must have smarter planning of urban transport than what exists—and that would require planning that is responsive to commuting motivations and travel activity patterns of the people living in the cities. In a blog post, World Bank urban transport specialists, Shomik Mehndiratta and Bernardo Alvim, write how, at the heart of such planning, is origin-destination (OD) data for urban commuters, and how Big Data—from call data records (CDR)generated by mobile companies—could be used to map out OD matrices at a fraction of the costs incurred in the traditional method of generating the matrices through household surveys. How this works is the CDR data, captured by mobile towers in specific locations in the city, give insights into traffic volume across routes, routes favoured during peak hours, etc, based on the location, duration and time of calls made on a mobile network. These insights can then be incorporated into laying rail routes, roads and constructing flyovers.
The Bank is working with Marta Gonzales, a researcher at the Massachusetts Institute of Technology, who developed a protocol to analyse CDR data to generate OD matrices for Rio De Janeiro Metropolitan Area in Brazil. Based on comparisons of CDR-based matrices for Rio and Boston (where the Bank was already working on the same), the experts found that CDR Big Data could be a reliable indicator of commute (home–office trips). Given such trips determine the viability of mass transit investments, the World Bank experts note, CDR Big Data could indeed help transport planning get granular.