You Say You Want a Revolution

Some say there’s a revolution in transport. But to have a revolution, you need revolutionaries.

Transport is certainly undergoing a transformation in the digital age, forging ahead rapidly in the buzzwords of ‘big data’ generation and the development of ‘Internet of Things’ connections. Transport has become ‘smarter’, i.e. more automated, more dynamic, more shared, and more personalised, such that ‘mobility as a service’ (MAAS) is billed as the ‘mode’ of travel of the future. But is MAAS the transport revolution of the 21st century in the same way that the train or the automobile revolutionised transport in the 19th and 20th centuries by creating mass markets of revolutionaries willing to adopt new ways of getting around and even new lifestyles because of the new transport technology?

According to Professor Cristina Pronello of the Université Technologique de Compiègne and Politecnico di Torino, MAAS will only revolutionize transport and travel behaviour if it is developed in a ‘user-centric’, transparent and integrated manner. Which, she said, means MAAS should not be developed and imposed on society by the big corporate players such as Google, Amazon, Apple, etc.

In a talk she recently gave at the University of Greenwich, she compared the tech company travel solutions to an app which was developed for Turin, Italy as part of a European Commission-funded project she led. She called her app an urban navigator, not a journey planner, and pointed to the depth of real-time, multi-modal feeds and customization it offered to users to support their travel decisions.

This ticked the user-centric and integrated boxes, but the Professor admitted difficulty both in establishing data-sharing arrangements with the various transport providers to build truly real-time integration and also in recruiting participating travellers to ensure user-centricity.

I couldn’t help thinking that Google Maps has none of these problems. Most people have it pre-loaded on their smartphone, and the company set the original standard for open data feeds. And if it has not quite the depth and real-time reactions of the app she discussed, I have met Google employees and am given to understand that they are constantly improving the multi-modal integration and accuracy of their mapping – journey planning – navigation tools through validated historic trips which users have themselves tracked and reported.

So what about transparency? There’s the rub. The European project embarked on numerous contracts, enforced a standard data format, and created an open data portal. Anyone with the skills could see where the data was coming from and how it was driving the app’s results. The tech giants are much more opaque, and most would agree that they are more motivated by the bottom line and intellectual property rights, than by a public service mission.

Yet, as was discussed in another presentation in Greenwich, traditional methods and local governments can fail to address social equity in their transport provision as much as corporations do. Although statistical methods tend to be based on assumptions about behaviour in the pursuit of explaining why travel patterns occur and how societal trends may influence those patterns, they are rarely then used to influence decisions to create more equitable patterns. And the models themselves are often black boxes, with calculations undertaken within proprietary software.

In contrast, the algorithms of data analytics are based on no assumptions at all. They seek to learn patterns to accurately make predictions, not to explain how or why those futures have come to pass. If such patterns are most likely to create a viable, successful Mobility as a Service, then transport practitioners should surely be turning to algorithms instead of assumptions, and perhaps also to companies like Google for their expertise – and for access to all those potential revolutionaries already using Google Maps or paying for multi-modal transport on their smartphones.

And yet. Maybe the companies of the digital age should only be supporting the revolution, not leading it. If they are producing the algorithms and finding the patterns, there is still a place for transport planners, land use planners, and civic society to shape those patterns to be more equitable, more affordable, more sustainable. The beauty of those algorithms is that if they happen to find a pattern in the shape of a virtuous circle, they’ll advertise it and disseminate it without asking why, and that really would be a revolution.

Buses Bounce Back

In my research into weather risks to transport supply and demand, I come across the word ‘resilience’ fairly frequently. I cannot always assume a singular definition, though. Some of the literature uses resilience to refer to low levels of vulnerability to extreme weather conditions or other disturbances; some to the presence of redundancy in a network, such that an alternative means of access can be substituted for any closure; others to the speed of recovery from a time of disruption until systems return to normal. Yet it all comes back to a similar idea. That like a rubber ball, strong yet flexible, designed to bounce back, something is resilient if it is strong enough to withstand the impacts of incidents like severe weather, and/or flexible enough to offer more than one option/way/route to users, and/or bounces back quickly to reasonable levels of performance.

It should be possible to look at any transport network, in any geography, of any mode, and assess its resilience. Ideally, multiple modes and geographies would be analysed in concert, as transport should act as an integrated system. Yet most studies of resilience or lack thereof in the transport discipline focus on only the road or rail networks, and only the private vehicles or passenger trains that use them respectively. This leaves multiple gaps in our understanding of transport resilience to different weather conditions, and one of these gaps is the lack of discussion about the resilience of bus services.

I cannot yet claim to be able to fill that gap, but I have just completed the analysis, write-up, and submission of a brief case study that perhaps starts to bridge it. And this case study indicates that buses might be one of the most resilient modes of transport available.

Furthermore, whilst there is some research into how people behave during disruption, it seems there is less consideration of their awareness of risk and resilience in the networks and services they are using, and how resilient this might make their behaviour. My short case study, however, provides some insight into the behaviour of public transport users, suggesting they are indeed resilient.

If you want to read my case study article, you’ll have to wait for its publication, but the key point is that where buses and rail run in parallel, the bus services are less disrupted, can divert if need be and still deliver the service, and can make up lost time more quickly than rail. The buses also seem to create redundancy, not just for themselves, but for the adjacent rail services. Finally, the number of bus trips rose sharply to and from places where rail passengers were likely to know that buses would be more reliable during the disruption.

I mentioned this to a former colleague, who suggested my discoveries should really be common sense. He also pointed out that the most vulnerable portions of the bus network were the depots and fuelling stations, which could easily be targeted for flood protection measures, for example, compared to the mile upon mile of train tracks needing improvements to resist those floods and ensure the operation of even a limited rail service.

Yet I later heard evidence that buses can be resilient even when the bus depot is inaccessible for many hours. In a talk I attended, a bus company manager explained how he, his drivers, and other staff improvised on the spot to keep a limited service running following a police closure of their depot’s access road. This won them great appreciation from their customers, and a flexibility, a resilience on the part of the not only the bus company and their passengers, but also the entire local community.

So an early finding in my PhD research: buses bounce back better than most transport options, their passengers know it, and the resilience of both buses and their passengers is rather unappreciated in wider transport research and practice.

Air Questionable Plan

 

The Government’s recently released consultation draft Air Quality Plan is more of an Air Questionable Plan. Why? I may be down to one blog a month these days, but this is a question I’m keen to answer.

It is often written that people struggle with environmental risks, because they are not imminent, proximate, and/or visible. That’s why people may feel climate change is an important issue to address, but struggle to be motivated. Air pollution is more local, but it’s potential, personal, health impacts may be even longer-term than the climactic increase in floods and droughts.

So it was easy for the Government to drag its proverbial heels until environmental groups forced its hand through the courts. Then they published a consultation Plan. Which I read. And, with my fairly extensive knowledge of local transport and my less extensive, but still greater than average awareness of air pollution, realised the Government was still dragging its heels. And its exhaust pipes.

Local air pollution is not a new problem. When I worked in local government, we were measuring, monitoring, and making plans to mitigate a decade ago. We even wrote a business case to introduce a Low Emission Zone. One that charged certain polluting vehicle types, but also invested in walking, cycling, and public transport. One not dissimilar to what the Government calls in its consultation document a ‘charging’ Clean Air Zone. But in 2010, as the Conservatives came to power, our business case was pulled. We continued with plans to improve sustainable transport, but we were not encouraged to resubmit any charging measures in the new rounds of challenge funding. Charging was part of the war on the motorist (including freight) that the new Government strove to roll back.

Fast-forward seven years, and it looks like anything too anti-motorist will still be discouraged. Or at least framed to ensure that possible political fall-out is local, not national. Charging is only to be implemented as a last resort. Somehow local authorities are supposed to encourage and support the mass retro-fit of polluting vehicles instead if at all possible. Or engineer their replacement with cleaner models. Even if many of the fleets in question are privately owned and operated. Local governments are also going to have to either use their own shrinking resources or compete for funding, spending money building business cases before they win, or don’t win, a penny.

In building the business case for Clean Air Zone measures, local authorities will also be aware that the Government’s guidance takes a very minimalist approach to the role of increasing the share of other modes like walking and cycling in improving air quality. It lumps all the alternative modes together as one measure in its list of eight , whilst four bullet points are given over to ways to reduce vehicle emissions without reducing vehicles. One of these four is: “Improving road layouts and junctions to optimise traffic flow, for example by considering removal of road humps”, a measure that is repeated as the first suggestion in a paragraph on “targeted infrastructure investment”.  What signal does this send? The safety of pedestrians and cyclists is secondary to improving the flow of traffic, despite traffic being the source of the pollution?

Furthermore, there is no mention anywhere that air pollution is measured as much by the population breathing it in as by the absolute amounts of pollutant present. That’s why so little of the strategic road network – less than 1% – is affected. There aren’t many schools and hospitals with motorway frontage. So why is there no mention of removing traffic entirely outside such sensitive receptors? Why not more pedestrianisation or “filtered permeability” with physically blocked streets to prevent through traffic?

I’m not saying that I have all the answers. And even this consultation document admits charging might be necessary. But neither do I think I’m jumping to conclusions to suggest that the draft Air Quality Plan favours the motorist over anyone who gets around in a different way, and pushes responsibility onto local governments, especially all those polluted, urban ones, many of a redder political persuasion. It makes it the whole commitment to reducing air pollution look rather… Questionable.

 

Road Rage at the Red Sea

Happy Passover, blog readers!

Have you ever wondered how the Hebrews crossed the Red Sea? The simple answer is on dry land, created by G-d’s miracle through Moses the prophet. But does that really explain anything?

Let’s picture the scene in more detail. The Hebrews, and we’re told they were numerous, have fled Egypt with their families, old and young, as many possessions and as much food as they could gather together at speed. There were probably some animals, maybe even carts, or perhaps wheelbarrows. They have come to the edge of the Red Sea and run out of land, never mind road. Do they queue up in an orderly line awaiting Moses’ miracle to enable them to cross? Unlikely.

In all probability, they were a milling mess, spreading out along the shore in both directions, in some areas crowded many bodies deep, in some areas standing solitary to peer out across the waves in the hope of spotting this promised land. So what happens when they hear the chariots of the Egyptian Army behind them and Moses raises his staff? Do they then re-group, line up with military precision? Unlikely again.

So how did they cross the Red Sea? Perhaps Moses created a bridge of dry land big enough for them all to walk abreast, but that’s certainly not how it’s shown in the paintings. Sure they were probably fine once between the towers of water on dry seabed. But before that? I imagine they were a seething, pushing, elbows-out, road-rage-driven, traffic jam. If you didn’t try to run round the edges and push ahead, then everyone probably cut in front of you, leaving the Egyptian warhorses nipping at your heels.

Or at least that’s the image that came to me last week as we sat queuing to get into the tunnel to Logan Airport in Boston, my aunt coming ever closer to missing her flight. Tunnels and bridges are often pinch-points, but in this case, behaviour played a part too. As if there were ancient, avenging Egyptians at their heels, car after car cut down the inside lane headed towards South Boston and then cut in at the last minute, pushing those waiting outside the tunnel ever further back in the queue, stationary and sweating.

And so, eventually, we had to do the same. With guilty conscience, we cut around, half wishing we’d done it earlier, half wishing we weren’t driven to being another of ‘those bastards’ as other drivers were probably swearing. My aunt had the barest half hour until her flight took off, and by the time she reached the gate, her ticket had been sold. She just managed to secure another empty seat at the back of the plane. Luckily it wasn’t oversold like the plane that made the news this week.

Yet it does make you wonder. Not only at the insanity of the design of the tunnels that access Logan Airport or the parallels that could be drawn between Boston’s peninsular, landfill airfields and the mooted Thames Estuary island airport, which would be likely even less accessible to the volumes of people it needs to serve. Nor necessarily solely at the challenges of modern driving with the limitations of GPS and traffic updates, which you expect will enable foresight and contingency planning, but often get you within a few miles of your destination, reporting a problem only when you are immovably stuck in it. No, it also makes you wonder at that ancient challenge, crossing the Red Sea, G-d’s people already risking G-d’s wrath with their own road rage long before the Golden Calf episode. Seems to me agetting across bodies of water was probably a problem even back then.

Anecdote or Endgame

When I tell friends, family, other mums at the school gate that I’m doing a PhD, they all ask me what my research is about. I’ve been working on my answer:

I’m looking at ‘big data’ to see what it can tell us about risks to how and whether people travel for work during severe weather events. That’s the one sentence version.

Sometimes it’s better to frame it as a question: What do commuters do when a big storm disrupts their usual journey to work, is telecommuting a preferred option, and what does that mean for how we plan for the more frequently extreme weather likely in the future?

That last bit is the aim, the purpose, the endgame of my research and why I believe a research council has agreed to fund it. I’m looking for evidence that might suggest that governments, businesses, and communities change the way they plan for and invest in resilience to severe weather and its impacts on infrastructure and property. And I’m looking in the new world of ‘big data’ because that evidence needs to be as statistically significant and scalable as possible, not just anecdotal.

Well, I’m still chasing the really ‘big’ data, but I have recently acquired some data on the transport impacts of Storm Doris on Thursday, 23 February 2017 in the Reading urban area. Trees fallen down, billboards blocking roads. Trains and buses delayed, diverted and cancelled. My data is sourced from local news reports, Twitter, and passenger numbers from Reading Buses on the day and on a more ‘average’ Thursday for comparison.

A few quick calculations and the results were suggestive. Passenger numbers were down during Storm Doris. Routes affected by diversions and delays due to fallen trees or other debris saw lower ridership than the ‘average’ day, but then so did other routes without noted storm-related problems. Did people stay home? Travel virtually or cancel their activity entirely? Were there map-able patterns?

I noticed that there were some routes which gained passengers. Why were more Vodafone employees on their dedicated services? The numbers couldn’t tell me. Why were more people on the long-distance route to Wokingham and Bracknell and on the Park & Ride service in that direction? A likely answer is that as the trains were even more affected than the buses, some people may have decided to switch. In which case, thinking of my endgame, perhaps Reading Buses should build that likelihood into their emergency planning for that route, run more buses. But was there enough evidence of actual cause and effect, of probability of recurrent behaviour to justify such an operational response?

I’ve been thinking about how much more evidence I might tease out from public data sources or a little more data from the bus operator. Are there patterns in the individual bus trips where the loss or gain of passengers was particularly noteworthy or could be matched to service disruptions? Is it worth looking at the type of tickets, the stops along the routes to get an idea of the demographics of who did or didn’t take the bus? Did anyone tweet their intentions to switch modes, to stay at home?

Yet with every dive deeper into the data, the falling probability of demonstrating statistical significance echoes ever louder. The passenger dataset was less than 90,000 on the average Thursday, falling by over 4%. The numbers on individual routes, different ticket types, different times, quickly descended into the hundreds or tens, even on the popular routes. My recently refreshed, but untested and uncertain statistical skills are already struggling with how to make a more than anecdotal comparison between one average Thursday and one disrupted Thursday during one storm in one urban area. How do I show that the most basic null hypothesis – that the storm had no impact on passenger numbers – is extremely unlikely, never mind look at any route in more depth to propose emergency service tweaks to the operator?

I have to face it. It will always be an anecdote. But it could still be an anecdote with an endgame.