Google maps walking directions from current location

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There are almost too many ways to get from London’s Charing Cross train station to WIRED’s offices in Hanover Square: head down into the tube for ten minutes on the Bakerloo line; step into one of several buses for a 15-minute ride through traffic; hop on a Santander cycle or Lime bike for a 12-minute cycle. Or just… keep walking, for those who can. It’s only 20 minutes via some of London’s prettiest streets.

Journey planner apps such as Google Maps and Citymapper cheerfully suggest all of the above, including the pedestrian option – but the routes on offer for the latter aren’t always ideal, sending walkers through tourist traps, down busy shopping streets, and along congested roads, a shame when there are lovely, empty side streets that get you there in roughly the same amount of time.

That could be set to change. Researchers are investigating how to model air quality to help pedestrians and runners avoid pollution, while others find ways to assess the beauty of a street or how happy it makes us. But two major hurdles remain: gathering the data and algorithms to churn through it all. Neither are easy tasks.

It’ll be worth the effort. Tanya Braun, head of policy at Living Streets, points to a growing stack of research that suggests – perhaps unsurprisingly – that for those who can, walking to work, or at least part of the way, reduces instances of obesity related diseases such as diabetes, improves mental health, and makes everyone living in the neighbourhood feel safer. "Travel-planning apps have the potential to improve health outcomes, but only if walking is prioritised in the user interface," Braun says. "Walking is an accessible, easy and free way of staying healthy."

There are plenty of countryside walking apps and some designed for tourists, and mapping and journey planners are getting better. Alongside public transport and paid-for micromobility options, Citymapper can now tell you which train stations are accessible to those with reduced mobility, while Google Maps highlights bike routes along less congested roads. As part of efforts to encourage more walking, Transport for London has backed Go Jauntly, an app that plans to add accessible routes between stations. But there’s more work to be done, in particular about accessibility, so those who can’t easily manage stairs aren’t given a route full of them, but also to show walking is just as easy as catching a cab or e-bike. “Active travel options, which cannot currently earn revenue for the app providers, can often be de-prioritised in app user interfaces in favour of linking through to private hire companies,” Braun says. “It’s important that travel apps improve – and not just for pedestrians that require mobility support.”

Researchers at London’s Turing Institute are working on both sides of the walking route challenge – the data gathering and the algorithms – as part of their work on air pollution. There, researchers are gathering air quality data and building predictive models, in order to be able to tell Londoners what pollution is likely to be at a given time and place.

Patrick O’Hara is a research assistant at the University of Warwick and a visiting research at Turing, and one of several researchers working at modelling air pollution and applying it to walking, running and cycling routes. In particular, he’s looking at building a tool to build circular routes for workouts. “First of all, you’ve got to deal with the data,” he says. “And secondly, you’ve got to use an algorithm that uses that data to find those routes.” Essentially, the air pollution modelling – or some other data set – needs to be combined with a path or road network.

That’s quite simple for one data set on one network with a single constraint, such as finding the fastest route for a driver in traffic. But adding in multiple data points and constraints, such as the fastest route with the cleanest air, is much trickier – and no urban walker wants to travel ten kilometres out of their way for a breath of fresh air. “If we’re just considering pollution, and don’t care about distance, were going to get a really bad route, because it goes too far,” he says. “If we consider pollution alone, the route is going to take a very long time. The problem is complex.”

It may seem as though journey planning apps for cars manage multiple data inputs, but even if taking into account traffic and road blocks, they’re still just optimising for journey speed. “They key point is that they don't have the second constraint,” he adds.

Adding in that extra constraint means it takes a much longer time to crunch the data and spit out a solution, with O’Hara saying it currently takes minutes or hours to get an answer on air pollution routing – that's a problem when most of us expect an answer from our journey planner apps within seconds. However, it’s possible to reduce the time it takes by settling for a good route rather than the best possible one, he adds, using approximation algorithms or heuristics.

All of this means that within a couple of years, we’ll be able to use Turing’s pollution modelling to predict the air quality at a specific time and place, but we’ll likely have to have a standalone app for planning our walk based on that data, rather than simply integrate it into an existing journey planner.

That’s helpful for people sensitive to air pollution, such as runners or those with asthma, but it doesn't allow the development of an app that pulls in different data sets – and there’s plenty of other considerations for planning the perfect urban walking journey planning app. Policing data could be used to suggest safer routes for walking at night; however, previous attempts to introduce safety data via an app called SketchFactor failed after the user rating system was called out for racism, suggesting not all data is best left in the hands of crowdsourcing. Sometimes it does work, however, and O’Hara points to running and cycling app Strava as a potential source of popular routes.

Another place crowdsourcing may work is rating the prettiness of streets. Chanuki Seresinhe is another researcher from Warwick working out of the Turing institute. She’s built an algorithm that can take any outdoor image and rate how beautiful it is, using neural networks that were trained by human raters. She had 200,000 images that were rated 1.5 million times on a website called ScenicOrNot.com. “I’m really interested in understanding the beauty in cities, because I’m actually looking at the connection between a beautiful place and well-being,” she says. “And, of course, most of us live in a city.”

ScenicOrNot has one photo per square kilometre of the UK, which isn’t quite enough detail for picking the prettiest streets in an urban environment. So she turned to Google Street View, applying her algorithm to the visual mapping system. “I can tell you where the beautiful places are on a street leve,” she says. “It’s not perfect, but it’s quite good.” If a location is on Google Street View, she can give it a beauty rating.

The neural network has learned to like places with greenery, she says — but there’s more to cities than tree-lined streets. While it can recognise buildings with a lot of character or physical differences, in particular open frontages versus big blank walls, there’s work to be done on the urban design. “One of the problems I have at the moment is the algorithm can’t tell the difference between types of architectural design,” she says. “[The algorithm] is looking more at the scene; if there's trees along the street, it will rate higher. If it’s a building that’s mostly concrete, it’s going to read lower — even if I think that perhaps the design of the building does deserve to be rated higher.”

Related research by Seresinhe suggests that if walkers can be directed down prettier streets, it’s good for their well-being. But there are more direct sources of data about where we feel the happiest, thanks to a project called Mappiness that tracks users’ mood and plots it on a map. “Twice a day, [the app] asks how you’re feeling and what you’re doing,” explains George Mackerron, a lecturer at the University of Sussex who develops the system. “And while you’re answering, it takes your GPS location.”

That data could be used to build an app that sends walkers via routes that make them happier, just as O’Hara’s pollution tracking apps send runners down roads with cleaner air. “We could do the same thing with happiness data… have a routing algorithm that prioritises places that people feel happy. It’d be quite a nice thing to do in addition to these other options around pollution.”

Having a bit of a nicer commute is at the centre of Likeways, an app being co-developed by Martin Traunmueller out of University College London. “As common route finding apps, such as Google or Apple maps, offer the quickest route to get from point A to B, they often guide the user via rather boring main routes with high motor traffic, and hence keep possible gems hidden in the dark that might be just around the corner,” he explains. “Likeways finds these hidden urban gems and includes them into the routing to turn a rather unpleasant commute into a pleasurable experience.”

The app analyses social media data to find interesting places such as a restaurant or cafe to take urban walkers, it’s not all about suggesting places to pick up a coffee on your morning commute. “While common location based social networks are limited to the rating and sharing of specific business venues, such as a bar or a shop, Likeways allows the user to 'tag' any geo-locations, such as a viewpoint or a tree,” he says. “This process establishes a location-based digital urban layer that the app uses to generate navigation routes.” In the future, Traunmueller hopes to add route safety as well as pleasantness into the mix.

The aim, he says, is to turn commuters into urban explorers, encouraging pedestrians to explore new areas of the city, rather than speed walk on by. The app remains in development; though it was first released in 2016, it’s been pulled ahead of a future relaunch. In the meantime, it’s up to us to explore and see what prettier, cleaner, and less congested walking routes we can find – it may make you late for work, but you’ll have a healthier, more interesting commute for it.

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