Predictive Analytics - Public Transport

Predictive analytics in public transport

Public transport managers around the world collect large amounts of data on a daily basis to better understand how individuals move from one place to another in cities through predictive analytics. The main mission of these officials is to collect all this information in order to study and understand it. These data are very important because with them it is possible to improve transport systems, anticipating possible problems and solving them before they occur. They are using the predictive analytics.

Table of Contents

These types of studies for public transport can have several uses and offer the possibility of developing more user-friendly and more efficient services. All this while promoting its use in large cities in order to move citizens a little further away from the dependence we have on the private vehicle.

Predictive analytics to know where my bus is

Using live information from the movements of trains and buses,the Swiss-German technology company GeOps and the University of Freiburg have created an interactive map of the most important transport systems in the world Thanks to this system we can see how the main cities of the world move. It is called the Travic Map and includes more than 200 systems from around the world, represented as colored dots that move slowly through the network. Although interactivity is mainly based on schedules set by the corresponding traffic authorities, the map incorporates live data when possible. This makes it possible for people to see the public transport systems of the cities where they live live.

This has shown that using predictive analytics you can extract the data to find solutions to transport problems that normally cannot be seen with the naked eye. For example, in Boston they have used predictive analytics to develop a picture of transportation operations across the city. It is similar to Travic but in it, the schedules, availability of parking and the flow of passengers all converge together.

Other companies such as Xerox have developed analytical platforms that filter anonymous information of users as they buy and use tickets every day. This information is presented with graphs that help transport managers understand and predict the movement of passengers,as well as their needs and adapt the system to demand.


Predictive analytics to know data about passengers

On the other hand, companies like the Mobility Analytics Platform (MAP) use data analysis algorithms and visualization technology to predict where passengers can disembark. It also forecasts the effect that occurs on travel by advancing or delaying schedules and even the consequences that the weather may have. With this type of data it is possible to optimize the service. In Australia, exactly in the city of Adelaide, this MAP system is being tested to improve its public transport system by analyzing how people move between different areas of the city.

Despite the great progress being made in these fields, cities remain slow to take advantage of data to improve their transport systems. According to experts, most authorities in charge of public transport simply do small surveys or try to guess the possible behavior of passengers.

Every day millions of passengers buy and use tickets to get around by public transport, creating an incredible amount of information about your daily mobility habits. With the implementation of these predictive analytics systems you can obtain real-time information with which it is possible to solve problems before they appear.

For example, you could see if a certain route is overloaded and add more buses that day. In addition, with the help of mobile applications, this information could be doubled, expanding the potential of these tools as well as their effectiveness, impacting everything for the benefit of users. Many experts of digital strategy believe that the future of large cities is based on the use of public transport, since the new generations cannot or do not see private vehicles necessary, so the optimization of this basic service is absolutely necessary.