Officials in Seoul had long searched for a transport system for low-income workers who commute late at night. Although a taxi ride was an option, it was a very pricey one, particularly for a commute on a regular basis. Low-income workers do not make enough money to take a taxi regularly, and taxi fares are considerably higher at night. Furthermore, since low-income workers tend to live on the outskirts of the city, taxi drivers often are reluctant to go there mainly for distance and security reasons.
These were some of the big challenges faced by policy makers in Seoul, a city regarded as a champion of public transportation. So what to do?
Part of the solution was the analysis and utilization of Big Data to come up with a suitable mode of transport that would serve the specific needs of late-night workers. The result was the creation of the “owl bus,” which operates late into the night until five o’clock in the morning.
In this context, Big Data has a considerable potential application in the transport sector, and for infrastructure development in general. In fact, World Bank and Korean officials will discuss on Tuesday, May 28 the theme “Leveraging Information Communication Technologies (ICT) in transport for greener growth and smarter development.”