Pedestrian Navigation… and the City

One of the most common buzz-words in an ever increasing smart world is the ‘walkability’ of a city. Walkability describes the pedestrian-friendliness a city offers to its population and hence, has great impact on the city’s environment and urban life quality: a high walkability-score decreases on one side motor traffic and on the other, increases physical activities and social interactions within citizens.

The way we walk through the urban fabric has changed in the last decade tremendously with the advent of digital mobile technology. People navigate through the contemporary urban environment via applications on mobile devices, such as Google Maps or Citymapper, making it easy to get around in the city on short routes very time-efficiently.

However, as practical as these approaches might be in terms of efficiency, they constitute a problem when it comes to the walking experience itself. Tourists, visitors or inhabitants of cities like New York, London or Vienna are often looking for a flaneur-esque experience (urban strolling) – they want to soak up the city and see hidden sights that are unique to the city they are exploring. The question naturally arises how technology can be designed to better support this kind of urban exploration in order to motivate pedestrians and support a city’s walkability.

Mentioned standard services give little attention to the walk itself. The location, landmarks and surrounding are often not included in the route description, guiding the user mostly via broad, noisy and stressful streets, instead of pleasant and more quiet, parallel backroads. In fact, these backroads, with “hidden gems” and venues, such as art galleries, small pubs, neat cafes or shops, are often locations where the actual urban life happens! Places like these would make the walk to an experience in it self and have great potential for walking motivation, but will be missed out easily by following common navigation approaches, degrading the walk to a spatial necessity.

Location Based Social Media… and the City

In recent years social networks, such as Foursquare or Facebook, have incorporated various location-based tools. For instance users can easily share their current location along with their opinion about near-by venues by using commenting and voting system. A popular example for such a system is the ubiquitous Facebook-Like-button, shop owners can use to represent their business on social media to their clients.

A Facebook-Like allows people, to create a “digital bond” between them and a certain venue that is represented on social media, providing them with steady updates and information about the place.

In doing so, location based social networks, such as Facebook or Foursquare, lead to the creation of a rich data set of geo-located user choices and crowd feedback sprawling over the cityscape.

Likeways: From Research to Product

With the above described problem of navigation on one side, and the freely accessible information about urban places on the other, we built Likeways, a mobile application that makes use of this data, translating it into the urban space to contribute to the walking experience.

The idea to this approach is based on my master thesis from The Bartlett – University College London (MSc. Adaptive Architecture and Computation), where I built a desktop prototype to run several user studies about usability and demand for such an approach (paper). As results were promising, I developed the desktop version further with a colleague into a first mobile prototype, in parallel to my PhD in Computer Science (ICRI on Cities, University College London). The prototype received an award that allowed us further development from of prototyping, up the stage where we are now – a product.

Likeways is now available for iOS and soon on Android.

Likeways: How it works…

The Likeways interface shows a map with the user’s current location. First, the user can choose on a swipe-in menu between various categories for places of interest s/he wants to see while walking (as for instance “Shops”, “Pubs”, “Museums”, “Restaurants”, “Galleries”… etc.).

After selection, the user defines a destination (the origin is the current geo-location of the user) and the route generation begins:

• Likeways access’ the Facebook database to retrieve information about venues along the way, according to the selection.
• Besides geo-location, Likeways also retrieves the number of “Likes” for each venue, indicating its popularity by the public
• Number of “Likes” is used by the routing-algorithm to influence the route: The more people like a venue, the more the route gets pulled towards it, and hence the more likely it is that the user will pass by.
• After the route generation process, two routes are shown on the map:
  • grey: the short, rather boring route as suggested by Google Maps
  • blue: the slightly longer, but more exciting route as suggested by Likeways
  • pins: show the location of each venue, used to generate the route. Pins can be switched off to increase the urban exploration aspect.

Challenges and future opportunities

Up till now we have used this approach in cities of different sizes and cultures all over the world. According to the density of population, we found differences in outcome. For instance, in small towns with a small number of venues represented on Facebook, our approach hits a barrier as the data is limited. Similar results we received also in countries where the social network is not available at all due to censorship, as for instance China. On the other side we face also challenges when there are too many Facebook venues, as for instance in the centre of London. As the route generation would take too long, we have to filter out venues from the process.

However, besides these technical limitations, the approach shows great potential to support urban walking, according to user feedback. At this point, we see it as solid base to build on as there are many features that might be useful to build in, such as including the walking time or opening times of shops for instance. Also, the data of use is not limited to Facebook but can take sources from other social media, tourist or traffic data as well, and hence, would allow Likeways to be tailor-made to specific user groups!

Enjoy exploring the city!