THE WAY WE ARE TRAVELING ON TRAINS POST COVID IS CHANGING – WE NEED TO UNDERSTAND IT MORE EFFECTIVELY

A UK tech firm has announced a new collaboration which aims to investigate how train passengers are traveling in the post Covid age.

TUBR, a deep-tech machine learning company, is working with the Rail & Station Innovation Company (RASIC) in an ambitious new scheme which seeks to better understand what the “new 9-5” now looks like.

The collaboration comes amid a revolution in the way we are traveling post Covid.

Since the height of the pandemic in March 2020, the number of people using trains has fallen by 25%. Whilst train travel has increased, the times and places in which people are traveling has changed dramatically.  This has been sparked by modern hybrid forms of working which mean many passengers are now traveling outside the traditional rush-hour period meaning more off peak travel and lower average ticket fares.

Dash Tabor, the co-founder of TUBR, a deep-tech company which is helping to predict the demand for rail services, said: “The way people are moving is changing. It is not always the case that carriages are crammed at 8am and 5pm. Instead, people are using the new found freedom bosses allow them to travel in at different times. We’re also seeing an increase in long distance travel and moving at all sorts of diverse moments in the day.

“We’re starting to see a recovery in the rail sector post-covid but the trends have changed and it’s vital we better understand it. That’s what this project seeks to do.”

The findings of the new project will allow operators to be more proactive and manage delays caused by crowding which can in turn reduce unnecessary expenses.

In their collaboration TUBR and RASIC will use AI-based technology platforms to investigate occupancy at 20 of the UK’s largest train stations, based on RASIC’s RDIS system.  This will allow them to provide highly accurate and granular predictions for the future which, in turn, can improve customer experience. These predictions show how many people will move through the station complex up to 21 days in advance, giving operators the insight they need to plan resources, manage flows, and enhance their offer.

Dash adds: “Accurate data can help prevent delays due to overcrowding on platforms, improve the flow of movement in the station and drive revenue to station shops by addressing travelers’ needs. They can help transport firms more effectively schedule staff and keep travel flowing.”

RASIC is a London-based innovation production house specialising in using technology to improve the rail industry and to improve the mobility experience. The organisation has designed and implemented delivery strategies that offer controlled, progressive improvements to the existing rail environment. RASIC currently has over 25 live innovation projects in the UK and across Latin America, with more planned.

RASIC Managing Director Marcus Mayers said: “Using data smarter is key to understanding rail user behaviour in a changing market, our work with TUBR has created another valuable insight to help operators respond to emerging trends by forecasting when stations will see greater usage and therefore provides actionable information to help deliver consistent service to passengers ”

Details of this new scheme come weeks after new data emerged which underlined the new way passengers are traveling post Covid.

According to analysis by the Centre for Policy Studies (CPS), the rise of working from home saw the number of people commuting five days a week fall to just 15 percent of pre-pandemic levels.

Total commuter journeys fell to just 45 percent of pre-pandemic levels, and only 41 per cent into London, according to the CPS data.

But five-day-a-week, peak-hour commuting has taken the hardest hit – with levels down by 85 per cent compared to pre-Covid levels, the think-tank said. The data is based on Office of Rail and Road figures published in March covering the last quarter of 2021. Commuter numbers are still more than 20 per cent below pre pandemic levels, according to a separate analysis based on comparing Google mobility data for May 12 to levels in February 2020.

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