As lockdowns ease, it's time to reverse ridership decline and make buses the mode of choice for everyone.
In the fourth and final part of our 'Bus Back Better' series (read parts 1, 2 and 3), James McCarthy, Head of Operations at CitySwift, explains how passengers can be placed at the heart of service improvement plans.
If the transit sector is serious about getting people back on the bus, passengers need to be at the heart of any post-lockdown service improvement plans. Operators should do everything within their power to improve the passenger experience.
This will not only help unlock congestion and promote economic growth, but it will also play a significant part in helping decarbonize economies and improve air quality in our towns and cities.
Getting people back on the bus will not only help unlock congestion and promote economic growth, but it can also play a significant part in helping decarbonize economies and improve air quality in our towns and cities.
But it's undeniable that society has changed since the arrival of Covid-19 – and will change even more in the weeks and months ahead as lockdowns loosen and society gets back to normal. The way we work, shop and play have inevitably changed for good.
That's where CitySwift's expertise can help. We were one of the first businesses to fully embrace and develop a platform to explore the world of passenger behavior.
This means we have a plugin-and-play system that's ready to go that can help bus operators and transit agencies get the very best from their bus networks in this new era.
Fully understanding bus networks is going to become incredibly important as we emerge from lockdown. People within the transit sector have known their networks like the backs of their hands for decades - and there's no denying the considerable expertise the sector has - but right now there's an incredible amount of uncertainty.
The CitySwift bus data engine can forensically analyze where riders are going – are they still traveling to and from city centers? Are they still going to and from business parks? Are they still doing it at the same times? There are network nodes that we had a preconceived understanding of before the pandemic, but they may not be the same anymore. It’s important to scrutinise those demand patterns.
One way the transit sector can compete with the private car is by offering competitive journey times.
The CitySwift platform can identify if there's demand for, for example, an express service, or whether resources would be better concentrated on certain segments of any given corridor in order to make a service truly 'turn up and go'. It means a better passenger experience by meeting the needs and aspirations of bus users, while also better matching the resource requirement.
Our bus data engine eats patronage and demand data and combines it with information from a variety of sources – would you believe it even digests how busy the local coffee shop is likely to be at 8am on a Monday morning or how many people are likely to pop out for a few drinks with friends after work on a Friday evening? All this in a bid to better understand buses!
So we have a good idea of the likely behavior of passengers from across society and we can identify networks that meet their aspirations and service their emerging travel patterns. But it's important to note that this data is purely 100% demand-derived – it is route agnostic. It is about the A to C journeys; not just the A to B. We are seeing where people are going to and from and it’s about changing the network to meet that need – and we’re using the very latest data and AI-derived insights to do it.
We are seeing where people are going to and from and it’s about changing the network to meet that need – and we’re using the very latest data and AI-derived insights to do it.
The world has changed. It’s clear that bus networks will have to change too. We have a unique opportunity to create bus networks that work for all and offer a compelling alternative to the private car. Data tools will be at the heart of creating that compelling alternative.