The following is a quick survey of new informational approaches to transport, hinging on individual behaviour and engagement via public data. We'll travel from wifi on buses to designs for timetables embedded in the fabric of stations, stopping off at trams in Google Maps and proposals for roboscooter sharing schemes.
Data, transported and shaped by the internet, is increasingly becoming a primary way that people expect to engage with public transport in particular. Engage, as in access and navigate through transport service information, but also explore and understand the transport service itself. This last aspect might sound initially far-fetched - “Why would people want to explore their transport networks?” - but many of these examples indicate that people do. They often go well beyond basic communications initiatives like integrated transport systems and into genuine two-way and many-to-many network-based interaction. Whilst they can do little to help if the eventual public transport service itself is poorly run, built over a well-run system (such as Helsinki’s or Zürich's) such systems might increase satisfaction amongst existing users and attract new users.
Further, engaging with the energy output of transport is something people may directly engage with too, to help shift behaviour. Studies elsewhere, such as Pacific NorthWest National Laboratory of the Energy Department indicate that when exposed to the effects of their behaviour in terms of domestic energy use (electricity, water, gas etc.) via simple PC-based feedback tools, people may change their behaviour, leading to a 15% reduction in peak load on utilities. (And more might be achieved than that, through more sophisticated and better designed schemes.) Will this carry across to transport energy?
So, here are transport systems where usage data has become available - or could become available - and is then built upon, as a way of exploring whether various ‘live dashboards’ of transport across a city will engender new levels of engagement with transport. And whether this will increase awareness of personal behaviour and impact on emissions accordingly.
Some of the examples will have been seen before, so I’d be interested in any further examples you might have of urban informatics applied to transport - please add examples/thoughts via the comment form at the bottom of this post.
A note on the importance of data
A key aspect here is to ensure that transport systems are generating rich data in real-time as a side-effect of their use I.e. not as a discrete activity, measuring performance occasionally, but that systems are in effect working as continuous broadcast networks, each node - tram, bus, bike, car - generating data about its behaviour (effectively they become large ‘spimes’, or aggregates of spimes). Having achieved that, we can measure behaviour and thus measure change. And then feed back information to users to enable them to measure their own change too. The first users of the data should be the transport networks, the public or private bodies that run or legislate them, and the public themselves. This last feedback loop becomes the most interesting, ultimately, as it not only makes the transport systems accountable for their performance, but also enables users to perceive, measure and change their own behaviour.
Each car, bus, tram becomes a node in an informational network, not just the transport network - and visible by the public. Moreover, by opening up this information, people can tinker with their own applications to monitor, explain, explore transport usage - the kind of open approach to data that has fuelled the rapid growth of internet-based systems. (Related: The Personal Well-Tempered Environment) People can engage further with the city, seeing it through the prism of transport, building stronger civic relationships.
Much of the innovation in terms of transport data is from private companies. Here’s a round-up from mainly UK and US sources, based on the work of Christopher Zegras of MIT’s Responsive City Initiative (as cited via MIT researcher supreme Fabien Girardin, who has helpfully collated and discussed many of these issues from numerous angles on his excellent site):
- Inrix: data provider from stationary sources, toll systems, 650,000 vehicle probes. They then clean and sort the data and sell to TomTom, Garmin, dash.
- Navteq - Traffic.com: road sensor network (the biggest in the USA).
- ITIS Holdings and TrafficMaster (cctv, fixed sensors, probes)
- TomTom Mobility Solutions: cellphone vehicle tracking project (with Vodafone).
- Traffic from cellphone triangulation: IntelliOne, AirSage, CellInt
- Public transportation real-time transit information and schedules: Hopstop, Transloc, mybus, nextbus, Google Transit
- Carbon Hero calculates carbon footprints (alongside many others)
- TomTom’s MapShare (user-generated maps for TomTom)
All of these rely on massive amounts of real-time data, then filtered and aggregated. The data used by most city and state governments, however, is often years old (Boston uses data from 1991, which is hopefully a worst case). Zegras suggests that most transport systems have not yet made started capturing this rich data, nor made coherent use of the data they do have. Public-private partnerships would be a good model, given the pace of the private sector’s innovation in this field, but the need for strategic overview and public responsibility lies with the state. Thus it is vital that governments retail full exposure to, and control of, the data.
An alternative approach to garnering data about mobility is that being explored by MIT’s Senseable City experiment, which uses mobile phone data to track the city in real-time. Given the near-ubiquity of mobile phones, this emerges as a statistically valid (aka near-enough) method for tracking movement. While the WikiCity Rome implementation is oriented more towards narrative, the potential for tracking movement - and therefore transport, and therefore transport energy - is there in the project:
“The Notte Bianca implementation allows people access to the real time data on dynamics that occur in the very place they find themselves in, in that moment, creating the intriguing situation that the map is drawn on the basis of dynamic elements of which the map itself is an active part … 'How does having access to real time data in the context of possible action alter the process of decision making in how to go about different activities?'”
Below, some example projects grouped into 10 categories, starting with an overview over transport systems, and then initiatives in specific modes of transport, from cars to walking via taxis, flight and more besides.
Perhaps the best case study comes from the best public transport system in Europe - as ranked by the European Commission - the Helsinki system, with nine out of ten residents satisfied or extremely satisfied. This is due to many aspects of their service, but a particular advance can be seen in their use of information - within buses and trams, but also at the level of the network itself.
“Every bus and tram in Helsinki and the surrounding cities of Vaanta and Espoo are being fitted with Linux servers and GPS units. Every bus and tram in the conurbation will not only become a wireless hotspot serving broadband internet throughout the vehicle - for free - but every bus and tram is visible on a Google map (the beta version is at tinyurl.com/2gftso) that uses the same real-time passenger information as the controllers in their command centre.”
“The Google map, moreover, is open, meaning that if someone wants to come and improve it or write some extra application, they are free to do so. Not only that, but every bus and tram stop in Helsinki is being fitted with small "near field information" tags that allow anyone with a Nokia cameraphone to take a snap of the tag and launch a Java application bespoke to that stop. This means that you don't have to have to take off your mittens or tap in tricky Finnish place names such as herttoniemenranta when it's -22C and you're faced with sleet's bitter sting.” [The Guardian]
These are all techniques to reduce time at the bus/tram stop and progressively increase time on the bus/tram versus other modes of transport. This is an informational overlay onto public transport that would help shift behaviour away from private transport.
The Guardian concludes:
“What most bus passengers want is a system that shares real-time information with them. Not just at the bus stop, but on our phones, iPods, laptops and websites. They don't want to go to the bus stop to find they have to wait 15 minutes - they want to find out how far away the bus is before they step outside. Now the controllers know where the bus is, soon the passengers will want to know too. How long will they have to wait?”
This indicates the base-level aspirations emerging around public transport now, over and above on-time, comfortable and affordable.
Note that the following map-based system - click to see buses and trams moving in real-time throughout Helsinki - is open. This is an example of this new civic engagement in public transport. Of course, if subsequent user-generated systems or displays become successful and well-implemented, they can be ‘adopted’ by the city, and made secure, resilient and reliable. It’s a common approach to innovation in the technology world.
Transport energy can clearly be displayed using the same techniques I.e. overlaid on these Google Maps-based real-time timetables. And this published to the mobile and personal platforms mentioned above, as well as on displays on bus- and tram-stops, creating an association between saving transport energy and public transport. Not even Helsinki is doing this yet, as far as I know.
Combining real-time data about the various modes of transport would enable this holistic overview of the city’s transport to be published, shared and discussed, leading to far greater engagement from the public. This, in turn, leading to potential behavioural change, particularly if conveyed with imagination, as a series of attainable goals against which progress can be judged on a daily basis. It could sit alongside reward/congestion schemes.
“JourneyOn is a unique journey planner for Brighton & Hove. The planner helps you find a route across the city and tells you the cost, time and the number of calories you'd burn whether you walk, cycle, take the bus or go by car. To start just choose your mode of transport from the selection or fill in your journey details below.”
Publishing the data in an open format, ideally via an API, would enable it to be usable on Google Transit. Perth has recently joined Google Transit, as the first representative of Australian cities. Interestingly from a transport planning perspective, the engineer integrating Perth’s transit data with Google noted the distinct advantage that Perth has in running the only fully integrated public transport system in Australia (in terms of ticketing, journey planning and timetable data).
Octopus Card, Hong Kong and Oyster, London
We often hear rather breathless descriptions of how the Octopus integrated ticketing schemes has extended into many areas of retail. But these aren’t just about ease-of-use and customer loyalty, any more than FlyBy and Tesco Clubcard are. They are far more powerful in terms of data generators, exposing patterns of use in transport networks, and even influencing patterns of use in transit - again, just as Clubcard has given Tesco unprecedented levels of information on consumer habits. As with London’s Oyster, such schemes would convey vast amounts of useful data on patterns of behaviour - suitably anonymised and with privacy taken into account of course.
In Albuquerque, New Mexico, the city commissioned Vancouver-based company Visible Strategies to use its See-It program (short for Social, Environmental, Economic-Integration Toolkits) to convey how the city was progressing in terms of sustainability strategies. This, on the premise that few citizens will actually read paper-based strategies in detail.
“If you’re interested in Albuquerque’s plans for its buses, for example, follow the “Greening Our Travel” goal to the “Vehicle Efficiency” strategy, where you can read about the fleet’s ongoing conversion to alternative fuels. You’ll also find a graph that evaluates the plan’s progress (on track!) and a form to send feedback to a city manager. “It has forced us to take a good hard look at what data we have and how we measure our success,” says Danny Nevarez, who works at Albuquerque’s Environmental Health Department.”
It relies on data from the city itself, and indicates a richer way of publishing strategy and conveying information. With a bit of imagination, this could be extended by opening up aspects of the data to enable others to re-combine it, and by embedding the displays in bus- and tram-stops etc.
Travel-time maps, correlated with house prices
“UK-based non-profit MySociety teamed up with Stamen Design to develop some innovative time-travel maps. The snapshot of the map that you see above shows where you can live in London with a commute between 30 to 60 minutes where the median house price is over £230, 000. As you adjust the sliders, the map changes in realtime letting you adjust the commute times from 0 up to 90 minutes and the housing price from 0 to £990,00. The Department of Transportation, who requested the work, is the map's center (and basis for the commute times).”
Analysing Madrid’s volume of traffic
These beautiful visualisations - called Cascade on Wheels - indicate two ways of modelling volume of traffic through Madrid’s centre. It’s based on a static data-set, but indicates an interactive system for exploring the pattern of behaviour over the terrain, in an almost tactile fashion. While the information itself could also be communicated in an Excel spreadsheet, and usually would have been for years, these new ways of visualising and handling the data do appear to add a deeper level of engagement - almost visceral - with the material.
One of the outputs is a sound-based interface, which is an interesting and under-used variant on exploring such data.
Steph Thirion, one of the creators of Cascade on Wheels, notes the importance of the visualisation:
“Most traffic mappings are realtime information for drivers, to help them trace their route depending on the current state of traffic. The broader view, which is representing the average quantities over time, is not so popular. That's a shame, because this is about something that affects every single inhabitant of the city, not just the drivers. And the existing maps that cover this subject usually have failed to make that data truly readable. So I wouldn't complain of a lack of data, but I think there's a blank space that is begging to be drawn on. I'd love to see more visualizations on this subject.“ [WorldChanging]
Here are a couple of short videos of the tool in action:
Car-rental models could be usefully stimulated in order to reduce reliance on private cars (in a sense, just as bike-sharing schemes have). Both ZipCar and Flexicar in the US have struggled to turn a profit, despite some popularity, and ultimately merging (with not great consequences, allegedly). However, in part this is due to the established players of Hertz and Enterprise picking up on the business model. (See also Smartdrivers and GoGet in Australia; Whizzgo and CityCarClub in the UK etc. Note that Whizzgo cars are exempt from the London congestion charge, hinting at the integration with these wider strategies.) These systems tend to increasingly rely on Google Maps and access/identification systems, and could publish data about usage, enabling it to be folded into the holistic model described above.
The founder of the US’s most successful car-sharing network gave a talk last year about seeing transport systems as ‘mesh networks’, connecting in real-time in order to optimise service.
“Robin Chase: Getting cars off the road and data into the skies". See also StreetsBlog.
“From my Zipcar experience and from watching congestion pricing played out in London and Stockholm, I've learned that money -- market pricing, or accurate reflection of pricing -- is what turns people's behavior on a dime. If we're serious, that's where we have to go. Marketing is everything and wireless technologies bring us to a totally different world of possibility. Zipcar and car-sharing is one example of how the ability to rent a car by the hour easily and therefore pay almost full car costs for that hour causes people to drive dramatically less. You don't run out and buy your quart of ice cream, because it's going to cost you ten bucks to buy that quart of ice cream. You say OK, I'll do without, I'll eat cookies, I'll pick up ice cream tomorrow.”
See also ride-sharing, by GoLoco, enabled via the web and social-software techniques.
How route choice can be affected by real-time traffic information.
“Route Choice Behaviour of Freeway Travellers Under Real-time Traffic Information Provision - Application of the Best Route and the Habitual Route Choice Mechanisms.”
This paper investigates route choice behaviour on freeways between Taipei and Taichung in Taiwan under the provision of real-time traffic information. This hints at the effects of analytical data fed back in real-time and displayed on-street.
“The results confirm that the thresholds for changing the inertia behaviour of drivers should be larger than the ones for choosing the best routes. In addition, the drivers are more likely to choose either the best or the habitual routes once the generalised cost savings are greater than the identified threshold values.”
Based on London’s and Stockholm’s experience, many other cities are also now considering congestion charging. (New York State has recently voted against introducing it, indicating a classic state/city split, perhaps, amongst other things.) Again, though, the interesting aspect here is how such systems generate date about transport in the city or state.
The technology behind London’s scheme has recently switched to IBM - there are no details thus far of plans for better feedback to users, or opening up the data and combining with other transit data, as in the idea above.
“IBM was involved in a tag and beacon trial in Stockholm in 2006 which covered 24km of the city, affected 350,000 car journeys per day and reduced car traffic by 25 per cent. According to the company, the city's bus timetables had to be redesigned because of the increased average speed of journeys. The trial allowed the city to vary charges throughout the day, with drivers paying the charge through a direct debit account as they passed the beacons.”
See also the variable pricing congestion charging system proposed as an upgrade of Singapore’s Electronic Road Pricing (ERP).
“The Singapore government has initiated a trial project to study the feasibility of a GPS based second-generation ERP system to meet the requirements of congestion pricing.”
All these systems rely on sensors generating useful data, that could be multiplied with the public transport data from other systems.
Kansas traffic monitoring
The Kansas City Scout offers visualisations of live traffic over their road networks, linked in to traffic cameras and signage displays.
In-car navigation systems
It’d be interesting to see cities liaising with manufacturers of sat-nav devices, not least to prevent the increase in accidents when lorries are led down roads not suitable for them, despite it being a quicker route. Could sat-nav systems in cities prioritise certain routes over others, to the benefit of the region as well as individual drivers? (See also Taipei/Taichung paper earlier on route-choice.)
A new edition of the traffic detector handbook describes the various sensor technologies available.
The webfront retail model: displacing car traffic through home delivery
This emerging model is being trialled in a few stores now: the customer visits the store, tries on the clothes (or tries out other goods), and then orders them for immediate home delivery (you actually pay a premium if you want it immediately and carry them home yourself). It’s effectively a “physical trial space for online shopping”, which plays on its sustainability credentials as well as convenience. It enables shoppers to be downtown on foot, bike or public transport and not have to worry about the car.
“Is it greener to shop on foot or online and then have the stuff delivered? Well, surprisingly (at least to me) the answer is generally yes. Sometimes it's much greener. The ecological cost of driving a number of online purchases in one truck (a truck, I might note, that is increasingly likely to itself be more efficient than some US cars) on a pre-set route (programmed to also be highly-efficient) is a small fraction of the ecological cost of driving to and from the store to get them yourself.” [WorldChanging]
See also Brand Avenue.
A reversal of the business model of Ikea and other big box retailers, pushing the urban downtown onto the front foot again. Supported by smart web-based delivery estimate systems (“Your package is 12 minutes away, on Birrell Street …”). Becoming known as the webfront retail model, these stores need only a small footprint, and therefore fit well into older shopping streets, laneways etc. Could this be something city governments could push, as a subtle way of increasing retail mix in urban centres and helping reduce individual car traffic in favour of more efficient home delivery models?
An MIT project, which is a functioning deployed version of their more innovative CityCar research project, is a foldable and then stackable scooter (rear wheel tucks inside front) being built by Taiwan-based SYM. The interesting aspect of the model is the distributed rental model, a la ZipCar. Each scooter has its own GPS unit, thus could be trackable (and capable of generating usage data)
“Developers originally envisioned charging racks distributed throughout a city, which could double as rental stations where users would buy a one-way trip. If SYM ever decides to take that leap, adopting a business model that’s a cross between services like Zipcar in the U.S. and the successful Parisian bicycle rental program, it could be the biggest endorsement yet of one-way, short-trip vehicle rentals.” [Popular Mechanics]
William Mitchell, leader of the Smart Cities group at MIT, suggests a slightly different model for the USA - with scooter rented for trips to destinations, and cars rented for journey back, so the scooters should be seen in the context of their wider CityCars programme. This is more ambitious but fascinating.
“By placing stacks in urban spaces and key points of convergence, the vehicle allows the citizens the flexibility to combine mass transit effectively with individualized mobility. The stack receives incoming vehicles and electrically charges them. Similar to luggage carts at the airport, users simply take the first fully charged vehicle at the front of the stack. The City car is NOT a replacement for personal vehicles, taxis, buses, or trucks; it is a NEW vehicle type that promotes a socially responsible and more effective means of urban mobility.”
Velib’ in Paris, Vélo’v in Lyons, and Bicing in Barcelona have proved hugely successful (all cities with significant road systems, as well as dense urban cores). And Velib’ is now moving to London.
Photo via Inhabitat
Data underpins both systems - in terms of access and payment - but the data on usage could be revealed better to users than it is. Again, Fabien Girardin at MIT has done some great work here:
“This kind of accumulated data can help people to grasp the availability and quality of the system over space and time (e.g. do not expect to encounter available bikes in the Eixample neighborhood on a sunny sunday or it is hard to return from the beach in the evening).”
His video available here. The patterns in the data tell the story of Barcelona on a sunny Sunday evening - the bikes moving from the beach, back to the city.
Velib’ has been mapped by Girardin in the same way:
These systems (when implemented holistically, with better bike lane access enabled alongside) have already been undeniably successful, creating a new engagement with the city. Data-based experiments such as these are also manifestations of this new level of engagement in public transport that the internet can engender.
“”Imagine the patterns and lessons to be found as the system learns more and more about how it is being used - a transportation and urban planner’s dream.”
Bike network 2.0
Boston appointed a ‘bike czar’, Nicole Freedman, and her team has used Google Maps to create a set of bike routes across the city, based on the aggregated data from actual routes that cyclists took across the city
“We found out where the actual desire lines are,” said Freedman, and has since extended the network to enable users to rate streets for bikes. It’s a little rudimentary at the moment, but shows the promise of such systems. Boston are building the city’s first official bike map from the results of the system.
Southern California has seen an influx of wifi-enabled buses (see also Helsinki, above). The Google Bus is a private system, but offers a similar level of service to that of Helsinki’s public network. Both set the bar for bus or light rail travel of the near-future (with laptops, there are issues when standing on buses/trams of course.)
“The company now ferries about 1,200 employees to and from Google daily — nearly one-fourth of its local work force — aboard 32 shuttle buses equipped with comfortable leather seats and wireless Internet access. Bicycles are allowed on exterior racks, and dogs on forward seats, or on their owners’ laps if the buses run full. Riders can sign up to receive alerts on their computers and cellphones when buses run late. They also get to burnish their green credentials, not just for ditching their cars, but because all Google shuttles run on biodiesel. Oh, and the shuttles are free.” [Wired]
Almeda County in California also runs wifi-enabled public buses now. Note the wifi is a free service.
There are some fears this might increase sprawl but they seem a little misplaced. Either way, in cities that already sprawl it’s a way of making public transport more attractive through information (particularly as phones become wifi-enabled, as well as laptops.) This is something that private transport cannot compete with.
Rethinking bus stops
MIT’s research project “Re-thinking the Paris bus line”, in conjunction with Paris RATP, provided a few prompts as to how to re-think buses and bus-stops in the context of urban informatics. Points 3 and 4 below are more do-able, initially.
- Self-Organizing Bus System
In the ubiquitously networked urban environment, the increasing possibility to control complex dynamic systems in real time with computers and to be seamlessly connected to portable devices allows us to design intelligently self-organizing bus routes.
- Reconfiguring the Bus
We can reconfigure the bus so that it can be structurally much more connected to the urban environment, to people and to city services. Moreover, by embedding electronic intelligence, sensors and communication systems in buses, we can escape the traditional bus design and explore innovative solutions that are more adapted to people's needs.
- Electronic Guimard
We suggest new designs for bus stops that can take particular advantage of electronic displays and create a unique character for Paris, establishing new urban identities.
- Neighborhood Concierge
Bus stops are not only entry points to buses, but also to local life in surrounding neighborhoods.
Mapping real-time trains traffic
The earlier Helsinki example above is based on the transport authority’s open approach to data. These two examples from users, centred on France and Switzerland, use published timetables in a more predictive approach.
That man Fabien Girardin says:
“Since (these) train operators do not disclose the actual location of a train, these services must use indirect ways to collect these data. Where Are Trains (France) parses online schedule boards of different stations such as the one of Paris Montparnasse. The position of the train obtained in real-time upon Arrivals and with at least a 1-h delay for departures. Then the system uses pre-builded time profiles to estimate the current location of trains by-passing potential stopovers. Similarly Train Map (Switzerland) uses train timetable, and does not yet show the actual GPS-positions of the trains. “But, as Swiss trains are almost always on time, most of the time the position is accurate”
“Every 15 minutes, I'm taking the realtime (not timetables) suburban rail info from IrishRail.ie, scraping it into a useful data structure, then writing it to XML. I then plot this onto Google Maps, with the help of the routes and stations data file.”
Public information design of timetables
Stamen Design in San Francisco produced designs for SOM’s new TransBay Transit Center and Tower, embedding real-time transit information into the fabric of the building.
“E.J. Marey famously demonstrated that a train schedule can be much more than a simple list of numbers and times—it can be deeply informative, rich in meaning and pattern, and a joy to use. The entranceway to the Transbay tower affords an opportunity to bring these ideas to the public in a lush new way, by using the walls of the building itself as an enormous indicator of upcoming transit activity as it passes through the terminal. Trains, buses and other transit types are tracked in this system, and their positions and times to departure are indicated by their distance from the outside edge of the building. A passenger approaching the station from the street can find out just how much time they have until their train or bus departs, without having to do the mental math of checking the current time versus a posted schedule which may or may not be accurate. Over time, passengers could develop a mental model of the transit system at various times throughout the day, and understand quickly whether they need to run to catch their ride or have time for a drink at one of the Transit Center's many cafes and restaurants.”
By opening up data, external designers can produce information design works of high quality. Of course, professional designers can be employed to embed such information into the fabric of buildings and places too. In this case, Stamen’s designs aim to create engagement with public transport and the city, while remaining useful above all, in much the same way that the Flinders Street Station clocks have become symbols for Melbourne. Again, this indicates a form of informational work possible with public transport that really doesn’t have a parallel with private transport.
The latest Very High Speed Trains (VHST) such as the Spanish AVE, provide wifi on the train. They aim to sell this to business travellers initially, but then make more widely accessible. Wifi is far easier to implement in trains than aircraft.
“Spain’s AVE trains feature Internet access with video and audio players, reclining chairs, conference rooms, superior cooling and air conditioning, and dedicated restaurant cars. What’s more, passengers are refunded their entire fare when trains are more than five minutes late (but don’t get your hopes up, AVE is on-time 98% of the time).” [Dwell]
As with the information design above, Stamen have also placed GPS locators in cabs in San Francisco, to produce the CabSpotting project, which provides new layers of analysis into cab movements in the city. While this appears to be more of an artwork/R&D piece than a useful real-time public service, it too indicates the creative potential in this data. If this were extended to extrapolate transport energy data, how could this be conveyed to the public?
And as above, but with ships - Sailwx. How to encourage this, make visible, and extend to map transport energy (would be interesting in context of food miles)?
Walkit provides a platform for user-generated walking routes in London, Birmingham, Edinburgh and Newcastle/Gateshead, including a set of new air pollution-aware walking routes, in conjunction with the City of London, UK’s environment agency and several inner-London boroughs.
Londoners are used to walking - as with many European urban dwellers - but it’s generally less common in many ‘New World’ cities in USA and Australia. There it could use a little help from services like Walkit. "Check out the map above - through several parks and ... with no regard for one-way streets" says one US-based site, breathlessly. "It even calculates calories and CO2 saved based on walking speed and compared to other means of transportation. You can even choose low pollution routes that avoid ambling near heavy traffic"
Finally, the following images are from two great posts at Pruned about piezo arrays and crowd farms. They discuss how pedestrian movement through spaces can generate small amounts of electricity via piezo arrays. They could also generate vast amounts of data about movement through a space, whilst usefully powering itself.