From What-If To Next Level: Big Data In Poland’s Transport

Warsaw, Poland’s capital, is a metropolis renowned for its rich history, diverse culture, beauty, and endless possibilities.

The city has a population of 1.8 million people closing in on 2 million and according to the European Union (EU) Commission, the city’s Gross Domestic Product (GDP) stood at €86.5bn in 2018, a figure that represented 17% of Poland’s national cake.

That said, Warsaw is a beehive of economic activity as espoused by publicly available data. In 2020, foreign arrivals were limited by restrictions put in place by the Polish government to curb the spread of COVID-19 but data shared by the Census and Economic Information Centre (CEIC) shows that Poland recorded 21.1 million visitor arrivals in 2019 compared to 19.7 million people the previous year.

Such data shows why authorities in Warsaw would like to ensure that everything is running smoothly and why public transport would be at the top of their priorities list.

Warsaw has one of the most efficient public transportation ecosystems in Europe ranging from metro lines, buses, trams, and local trains.

Buses in Warsaw, Poland. The Polish Capital has one of the most efficient public transport systems in Europe
Buses in Warsaw, Poland. The Polish Capital has one of the most efficient public transport systems in Europe. Image Source {Warsaw Tour}

The city’s public transportation system is unique such that every bus, train, tram, or metro line is identified by a number, letter, or a combination of both, a system designed to ensure orderliness and effectiveness.

In this article, we will go beyond listing the different types of transportation systems in Warsaw as we will tell you The Role Big Data is Playing in optimizing those systems for the benefit of the residents who use public transport.

Warsaw’s Public Transport Systems

The city of Warsaw has an internal transportation system. The different public transportation systems in the city include two metro lines popularly known as the M1 and M2. Also at the disposal of the city’s residents are tram systems, buses, and local trains.

According to the Warsaw Public Transport Authority, there are over 1500 public transportation units that run across the city. The authority further notes that most transport lines operate between 5 am and 11 pm.

After these hours, buses ferry passengers on each route twice an hour.

Trams

Trams are a common means of transport in Warsaw. As stated earlier in this article, every means of public transportation in Warsaw is identified by a number, letter, or combination of both.

In the case of Warsaw, Trams are numbered from 1 to 79. Numbers 1 to 39 denote the basic connections while lines 40 to 49 operate at specific times of the day or week especially during peak traffic hours.

Trams operating in the Warsaw City centre. As seen in the image above, the trams are denoted by numbers to differentiate services & deployment
Trams operating in the Warsaw City centre. As seen in the image above, the trams are denoted by numbers to differentiate services & deployment. Image Source {Leszeck Peczynski via Warsaw Public Transport Authority}

The trams denoted by the remaining numbers 50-79 operate on special or substitute lines.

In the event service interruptions (failure or breakdown) or planned works occur, tram traffic may be halted and a substitute means of transport is introduced. In most cases, the substitute means of transport are usually buses denoted by the letter “Z” combined with a number e.g. “Z-6”.

Trams are preferred because they are environmentally friendly as they don’t release emissions into the atmosphere.

One of the ways Big Data is being used in Warsaw is through movement analysis which is used to plan and improve Tram Transport in the city.

This is best captured by the Vavel Project report jointly prepared by the City of Warsaw, Orange Polska (Telecommunications Company), and The Warsaw University of Technology. The project is supported by the European Union’s (EU) 2020 research and innovation program.

Vavel stands for Variety, Veracity, and Value in handling multiplicity of urban sensors.

The idea behind the project is to revolutionise the capacity to deploy urban data in applications that can sense and act on citizens’ needs and improve the quality of life in urban areas by analyzing a big number of multiple data streams.

The Vavel project involved collecting data from 400 trams, storing the data, processing the data, and then exposing the processed data to multiple subscribers.

During the project, the tram data was used to create an intelligent transport planner and come up with personalized services for citizens.

Buses

Buses in Warsaw identified by the numbers 100 to 399 are seasonal lines that operate only during specific times of the week. The seasonal lines are less convenient because they pick and drop passengers at all stops.

Buses denoted by the numbers 400 to 599 operate at a quicker pace and do not stop at low traffic areas.

A bus operating in Warsaw, Poland. Buses denoted by the numbers 400 to 599 do not stop in low-traffic areas
A bus operating in Warsaw, Poland. Buses denoted by the numbers 400 to 599 do not stop in low-traffic areas. Image Source: {Leszeck Peczynski via Warsaw Public Transport Authority}

There are also Express buses that primarily focus on the major transport line. They are denoted by the letter “E” alongside the number that shows them as express lines. These buses make it seamless to travel from the outskirts of Warsaw to the city centre and vice versa.

The buses that operate outside the Warsaw main zone are denoted by the numbers 700 to 899.

Big Data is also used to improve bus transport in Warsaw. In a similar fashion to the trams, the VaVel project collected data from 1,800 buses that operate in the city during peak hours

The project deployed the use of the Apache Flink- Vehicle Movement Analyzer, an application that combines statistical data sets and event streams of vehicle location data with the view of running real-time computations and notify commuters about important information such as bus positions compared to the timetable and vehicle delays.

The input data in the application consists of real-time information of the buses absorbed through Apache Kafka and then enriched with timetable data (GTFS files).

As elaborated by the example above, Big Data has made it possible to create efficient transportation schedules and put in place Intelligent Emergency Response systems leading to efficient bus transportation in the Polish city.

Metro Lines

Warsaw has two subway lines: M1 and M2.

The M1 connects Urysnow, a district located south of Warsaw, and Bielany, a district located North West of the Capital, and cuts through the city centre (Śródmieście).

The M1 Line in Warsaw, Poland
The M1 Line in Warsaw, Poland. Image Source: {Iber Campus}

The second subway line (M2) links Wola, a district located West of Warsaw with Praga, a district located on the East Bank of River Vistula.

The M2 metro line in Warsaw, Poland. The city has two metro lines
The M2 metro line in Warsaw, Poland. The city has two metro lines. Image Source: {Railway Gazzette}

The metro lines operate between 5:00 am and 1:00 am and between 5:00 am and 3:00 am on weekend nights (Friday & Saturday) at a frequency of 15 minutes until the next metro arrives.

When service interruptions occur i.e natural disasters & breakdowns, extra buses are dispatched to ferry the subway riders. These buses are denoted by the letter “Z”.

As per the report commissioned by the European Union, before the VaVel project started, the city of Warsaw was using a simple transport planner which was part of the ZTM website and only offered trip planning services based on static timetables.

After the implementation of the project, it became possible to plan useful services by applying newly acquired data types. It is now seamless for these sets of data to be centralized, becoming open data for developers and the Trip Planner application.

Big Data is also being used to plan Warsaw metro line journeys intelligently. For instance, it became possible to calculate and show the route to the defined destination based on user-defined preferences including the actual and predicted information. It also became possible to show alternatives to metro transport like bike stations.

Local trains

The Szybka Kole Miejska trains popularly known as SKM, in abbreviation, operate above ground, unlike the metro lines. They are denoted by the letter “S”.

They operate on four lines integrated with Warsaw’s public transport system complementing the metro network while providing good connections with suburban towns from which people commute to Warsaw every day of the week.

One characteristic of SKM trains is that they run every hour on average.

The SKM commuter train picks up passengers in Warszawa Stadion 2 in Praga, Poland
The SKM commuter train picks up passengers in Warszawa Stadion 2 in Praga, Poland. Image Source: {Chris Benson via Twitter}

Despite low operation frequencies, the SKM trains have a huge impact on travelling times, most notably in the districts that are further away from the city centre.

In the case of SKM trains, Big Data has been applied to notify commuters when a delay has been predicted, show user position on the map, and show important static public transport information such as stops and train station entrances via various apps.

The Smart Way

The key question when it comes to Poland is how the country can make its public transport better.

The whooshing of the sleek tram, the smoothness of the country’s metro systems, and the organization of Warsaw’s bus transport are a testament that the right foundations are already in place.

But good is never enough, especially for thriving economies.

With populations growing and the dynamics of public transport always shifting, a smarter solution is required.

That’s where Big Data comes in.