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Transport providers are facing the challenge of social distancing at train stations.
Transport providers are facing the challenge of social distancing at train stations.
( Source: gemeinfrei / Unsplash)

COVID-19 How can technology help with social distancing in train stations?

| Author / Editor: Cate Lawrance / Isabell Page

Transport providers are facing the challenge of social distancing at train stations. Technology is being deployed in a number of interesting ways to gain an understanding of people flow and social distancing.

COVID-19 lockdowns have meant that train and rapid transit stations around the globe have seen much less traffic than before. Now, with the gradual lifting of restrictions, travellers are returning. Yet the need for social distancing remains. Managing pedestrian flows within stations (especially underground and on the platform is a challenge. Reduced transport means increased risk during dwell times on crowded platforms.

However, before the pandemic, operators typically relied on experience and historical data to get a sense of station arrival, wait times and train usage. And yet, there was little knowledge of the true time passengers spent at the station before departure and after arrival, let alone when they entered, exited or moved around.

While transport providers are focused on cleaning (San Francisco, New York), temperature checks (in China), and compulsory for masks (Berlin, London), and floor markings to denote appropriate social distancing, technology can play a vital role in helping operators understand, predict and respond to station traffic. In response, transport providers are currently deploying a range of technological solutions including sensors, cameras, machine learning and automation to give operators a real-time, reliable overview of passenger volumes and movements, and increase staff safety.

Live AI embedded dashboards, heatmaps andalarms

Veovo has created a platform that enables rail providers to understand how people move into, out of and between stations, average wait times, and even occupancy on trains. It monitors crowd density in specific areas, such as concourse, stairwell, platform and carriage, and can be expanded to provide station-wide density and flow insights.

It uses live dashboards and heatmaps, according to social distancing regulations, to monitor crowd movement patterns and area size. Sensors and 3D cameras also count people and track movement in real-time. Threshold breaches trigger alarms and automated actions, like closing turnstiles.

Alarms and actions are triggered when threshold limits are reached, enabling rapid responses, like directing passenger flows and updating digital signage. Operators are also able to monitor sanitation and direct teams to where cleaning is most needed.

Commuter WiFi Data for Real-Time Analytics

Transport for London ((TfL) have been collecting depersonalised Wi-Fi connection data since July 2019. It's harnessed existing Wi-Fi connection data from more than 260 Wi-Fi enabled London Underground stations to understand how people navigate the network and help provide better, more targeted information to its customers as they move around London, helping them better plan their route to avoid congestion and delays. The data is also made available for app developers, academics and businesses to create new products and services.

The TfL aims in the future to use the data to issue an early warning via the TfL website and social media channels about congestion at ticket halls or platforms, which will allow customers to alter their route - this would also prove helpful in the time of COVID-19.

Sensors, alarms, facial detection and wearable tech

In Belgium, transport provider Infrabel has taken a different track - pivoting prototype tech in response to COVID-19 in support of their staff. Prior to the pandemic, they were working on two projects focused on worker safety:

  • The use of sensors to recognise if employees are wearing personal protective equipment, such as safety glasses or gloves
  • A fall detection system to detect scenarios such as a technician who has fallen onto the tracks.

Currently, their usual team of 30 workers per shift is reduced to 8 and a mandatory 1.5 metres between colleagues. A sensor permanently scans the room and machine learning is used to detect movement and Ultra Wide Band (UWB) transmitter wristbands are used to measure distance - they vibrate, send an audible signal, or blink if the wearers are too close to each other.

They're also using facial detection tech to determine if workers are wearing nose and mouth protection, or wearing it correctly. Hallways only allow walking in one direction to reduce contact. A bit extreme and too big brother at work? Sure, but significant numbers of transport workers have died from COVID-19 - many who were without access to PPE.

Software to monitor and direct people flow

PTV creates traffic planning software to help transport planners plan transport strategies and solutions. They are currently in discussion with Dr.-Ing. Klaus Bogenberger, Professor of Traffic Engineering at the TU Munich and are considering whether passengers should be guided right from the track and before they embark to the entry doors of the tram or train where they can board and be transported in the cars sorted by destination station. Of course, it's unclear how this would be communicated to passengers, wayfaring is not always effective and it's something that may be hard to enforce.

Social distancing is no easy feat. It's pretty much the antithesis of what public transport does - transport large groups of people efficiently. It's also incredibly difficult to reinforce and untenable to expect ticket controllers and other personnel to undertake the task. Further any restricted use needs to be complemented by service offerings of the private sector and smart mobility transport providers, some of whom will be sitting on idle capacity and would welcome the partnership. None of this is easy, but tech innovation might just be able to help.