Fusing MOTcellular and smartcard data

PI: Eran Ben-Elia

Researcher: Bella Demetreyeva

Funding: Ministry of Transport – Chief Scientist Office   2016-2018

Increasing the patronage of public transport (PT) is an important goal of transport policy. In recent years there is a persistent decline in PT use and increase in private car use. There is lack of information and data on the spatial distribution of travel demand both for PT and car users. This information is essential in order to generate an up-to-date picture of current trips and the potential to shift to PT.

In this novel research project we employ and integrate two BIG DATA sources:

  • Data on trajectories derived from the mobile phone telecommunications network;
  • Real PT trip data from smartcard transactions.

By developing algorithms for data fusion and data mining we will be able to analyze and understand the network’s level of service:

  1. Paths that are not served by PT and conducted mainly cy car;
  2. Paths with excess supply, served by PT but with low patronage;
  3. Paths with excess demand where trip rates by PT are high but service is low and improvements are necessary.

The research methods we will develop will be a turning point in establishing novel methods for level of service evaluation, will contribute to improving the PT planning process and necessary reforms in metropolitan areas and will eventually allow increasing PT usage in the long run.