Cycle helmets provide an opportunity to integrate the idea of Head-Up Displays (HuD) into cycling. There are already a number of ski goggles on the market with integrated HuDs. These are generally for 'push-notifications' which deliver online content, much like Google Glass. However if these displays talked to the city around them—if they knew where the cyclist was and what they were looking at—they could give much more subtle spatial and contextual information that builds on the surroundings of the cyclist. Learning from observation and our own experience, we see that cyclists often take bearings when paused at traffic lights—this interface could essentially simply provide the next direction, reinforcing the journey. We also feel that the visual nudge implied here, using the fabric of the city itself, is more akin to how cyclists move and navigate—a more fluid movement through and sometimes across the streetscape, as opposed to the very directed navigation delivered for drivers.
Last year we built a prototype called Cities Unlocked, working with Microsoft UK, Guide Dogs for the Blind and others. It delivers a 3D soundscape to people with sight loss to help them navigate the city, via a headset. The headset was fitted with sensors and gyroscopes for accurate head positioning, but also was 'talking' to GPS, beacons, wifi and location-based services via mobile to triangulate accurate positioning and derive contextual information. See more about the project here.
The second prototype builds on the first. Using the same HuD, it sketches an idea of how a a visual language of augmentation might help to develop the "imageability" of places and moments along a journey. Imageability is a term coined by groundbreaking urban planner/designer Kevin Lynch to describe the process by which we learn how to recognise and become familiar with our environmental surroundings and learn journeys. His research—described in his classic text "The Image of the City" (1960)—showed how landmarks and distinctive spatial characteristics help us learn to 'read' and learn places. These build a stronger image of places, journeys and spaces in our minds' eye. Developing technologies which enhance this visual learning—essentially, teach us to read the city—could be much more fruitful than developing technologies which subtract from our abilities to navigate unaided. How many of us now rely on a little blue dot on a map? And what do we miss when we're walking through the city looking down at our phone? On a bike, we particularly need cyclists to develop a heads-up stance, looking at the environment around them, rather than down at a phone. This prototype explores how technology might support a learning process based on imageability, such that the device and its interface essentially disappears over time, and the rider pays attention to the city around them. As above, we speculate this interface would be used intermittently, taking bearings every now and then, rather than being continually present.
We have also speculated whether richer environmental information could influence route choices for cyclists. A device that indicates pollution levels on streets ahead could support cyclists making more informed choices about the healthiest routes for them to take. Air pollution can be very bad on many London streets because of the 'canyon effect', with cyclists vulnerable to fumes in central traffic lanes. Nudging cyclists onto the back-street network could be healthier and potentially safer. Another project of ours—Sensing Cities—is developing a low-cost distributed air quality sensor network, enabling real-time data about air quality to be streamed from the street. Such a network at scale would make these kinds of choices available to riders. "Straight on is quickest—but the air is cleaner if you turn left." Again, we anticipate that any such prompts need to be delivered in a 'glanceable', almost ambient interface, so as not to interrupt the rider's attention.
In London a major cause of cyclist fatality is from 'heavy goods vehicles' (HGVs) turning left across their path. Yet machine-to-machine technologies could enable HGVs or buses to 'spot' oncoming cyclists. Simple projectors, via laser or equivalent, installed on such vehicles could detect and project the outline of their blind spots into the path of oncoming cyclists. This could enable a safer environment for cyclists—something to prototype and test. Other technologies being explored by researchers for this use-case are proximity sensing, radar and sonar.
The final prototype we developed was a very simple system for urban bike-sharing schemes, such as London's. By choosing to enter the destination at the docking station, a simple indicator, mounted on the handlebars or basket, would help keep the cyclist on path to that destination, giving minimal information but signalling any wrong turns. The device could locate itself via GPS, or use the rider's mobile phone to do so. (Key questions here, over and above battery-life, robustness and accuracy issues, would be how it links with third-party services such as Citymapper and what to do if the rider does not have a smartphone.) Again, our intent was a light-touch 'glanceable' interaction, rather than motorist-style arrows and directions. Also, understanding the particular context of bike-sharing, we prototyped this as a detachable device (actually modelled on a mobile-phone attachment for the bike-sharing scheme), something that a regular user might carry with them and clip on as required.
All these ideas are merely sketches of potential future products and services. We know that the best way to increase cycling activity in cities is to deploy connected, continuous, consistent and quality 'hard infrastructure' for cycling. These are suggestions of devices that could work on today's roads as well as helpfully augmenting future infrastructure.
Can we create early demonstrations of our future connected streets with cyclists to see how the dynamics of the connected street might play out? Might machine-to-machine communication change the necessity for separation of functions, enabled by a more connected street? Might the street environment be safer, easier and more harmonious when cars, bikes and people can all sense one another's presence? What about issues of access, resilience and robustness? We feel contemporary 'Internet of Things' technology has a lot to offer here—the question is how.
Speculating how the 21st century connected street might look, feel and behave may be key to better understanding how connected technologies could address some of the conflicts and tensions inherent in today's streetscapes.