Therefore, solving urgent urban transport problems in these cities requires us to think outside the box. Fortunately, the rapid development of ICT-enabled approaches provides a great opportunity to optimize and enhance the efficiency of existing and new urban transport systems, at a cost much lower than building new infrastructure from the ground up.
While we have not been significantly involved with such services thus far, a recently appointed mobility secretary in a big Latin American city has asked us for support on developing an approach to the shared taxi industry, as part of a "Smart Mobility" strategy for the city. In that context, we wanted to start a conversation on optimal strategies for cities to be able to welcome and foster such innovations, while still capitalizing on the opportunity to create value for its citizens.
Photo: Sam Kittner / Capital Bikeshare
Recently, I was invited to join a panel on the sharing economy moderated by Prof. Susan Shaheen at UC Berkeley, focusing more specifically on shared mobility.
The panel acknowledged that shared mobility is already transforming the mobility landscape globally, but could go a lot further in increasing the sustainability of urban mobility systems. The panel identified a number of key research gaps that we need to pay close attention to if we want to create a policy environment that is conducive to mobility innovations. Three that I want to highlight are:
- Supporting open data and open-source ecosystems is critical considering the tremendous potential of open-source software and data-sharing for improving transport planning, facilitating management and providing a better experience for transport users (for more detail, please see my previous blog on how the transport sector in Mexico is being transformed by open data)
- Looking into shared-economy solutions for those at the bottom of the pyramid – solutions that don’t require credit cards and smartphones as prerequisites (see this blog on the bike-share system in Buenos Aires for a good example)
- The world of driverless cars is coming – which, depending on how policy responds to it, could spell really good or really bad news for the environment: if such technology is used primarily in shared mobility scenarios, it could greatly reduce the environmental cost of motorized transport; on the other hand, the possibility of “empty trips” with zero-occupancy cars could exacerbate the worst elements of automobility (see Robin Chase’s blog in The Atlantic Cities for a great discussion on this). That is why it is critical to create a policy environment that appropriately prices the ‘bads’ of congestion, accidents and emissions while steering the world of driverless cars towards sharing and resource conservation.
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On a recent trip to Mexico City, I had the pleasure of participating in three events that really brought home the transformative power of the open data and open source eco-system that is becoming an ever more important element of our work in transport.
First I joined the Secretary of Mobility for Mexico City to inaugurate an open data-based system for alerting public transport users in this city of 8 million of any disruptions to the city’s multimodal transport system consisting of an extensive metro system, a suburban rail line, 5 lines of the Metrobus Bus Rapid Transit system (BRT), an electric trolley system, as well as a substantial publicly operated bus system. The alert system was built using open-source software on an open standardized data set of schedules supported by the Bank last year (read more about that initiative led by my colleague Catalina Ochoa). Not only does this service deliver value for Mexico City commuters immediately, but it also allows any other city that has its data organized in a similar standard GTFS (General Transit Feed Specification) format (over a 1,000 cities do) to use the same code developed for Mexico City off GitHub, a web registry. Moreover, the open standardized formats let developers in Mexico City or elsewhere build apps that use this information. The market for these applications is potentially global, spurring innovation for user-oriented applications in public transport: there are already many hundreds of GTFS based applications.
For fun, suppose you were a software developer, and you came up with a terrific idea to communicate public transit information. For example, imagine your city experiences frequent floods, and you have devised an automated system that sends SMS texts to passengers, advising them of alternative transit routes during emergencies.
How much revenue do you think you could earn for that software? How many people could you positively impact?
What if I told you that today, by taking advantage of one tiny revolution in open data, you could take those numbers and multiply them by 350, turning $100,000 into $35 million, or 1 million people into 350 million? Sounds pretty good, right? If you are in international development, sounds like a promotion…
The other day, my colleague Roger Gorham, a transport economist working in Africa, shared with me an interesting story. He was in Lagos, meeting with stakeholders about setting up public-private partnerships for transport initiatives. One meeting revealed that, in an effort to improve service, a private entity had invested in new taxis for Lagos and in each had installed a GPS unit. This little revelation may not seem interesting, but it was very exciting to Roger, who also learned that the company has amassed more than 3 years of GPS tracking data for these taxis (which, incidentally, troll the city like perfect probes, nearly 24 hours a day, 7 days a week) and that this data could be made available to him, if he thought he might make some use of it.
Now, if you are reading this blog, chances are that you realize that with this kind of data and a little analysis, we can quickly and easily reveal powerful insights about a city’s transport network – when and where congestion occurs, average traffic volumes, key traffic generators (from taxi pick-up point data), occurrence of accidents and traffic blockages in real time, and even the estimated effects of congestion and drive cycle on fuel efficiency.
As Roger said, “They are sitting on a gold mine and don’t even know it….”