In recent years, a variety of forces (economic, environmental, and social) have quickly given rise to “shared mobility,” a collective of entrepreneurs and consumers leveraging technology to share transportation resources, save money, and generate capital. Bikesharing services, such as BCycle, and business-to-consumer carsharing services, such as Zipcar, have become part of a sociodemographic trend that has pushed shared mobility from the fringe to the mainstream. The role of shared mobility in the broader landscape of urban mobility has become a frequent topic of discussion. Shared transportation modes—such as bikesharing, carsharing, ridesharing, ridesourcing/transportation network companies (TNCs), and microtransit—are changing how people travel and are having a transformative effect on smart cities.
Walking & Biking: High tech understanding of low tech solutions
Sometimes smart cities have simple solutions at their disposal – if they just view their data slightly differently. Walk Score recently released their updated rankings of bikeable, walkable, and transit-oriented cities:
- 10 most bikeable large U.S. & Canadian cities (>200,000 people). The data on bike lanes, hilliness, and connectivity are all easily shown with elegant “heat maps”. An interesting inclusion in their scoring methodology is a “bicycle mode share” metric, which tries to capture the social network effect of biking. Rather than relying only on data about the built environment, the metric also attempts to measure actual cycling activity, often showing that there are “hot spots” in certain neighborhoods of cities aside from where the bike lane networks are.
- 50 most walkable largest U.S cities, as well as Canada and Australia. This ranking relies on an algorithm that gives higher weighting to proximity to amenities within .25 miles and zero weighting to amenities further than one mile. This metric is used by the real estate industry in promoting walkable, livable neighborhoods.
- 25 top-ranked public transit systems in the largest U.S. cities, measured based on “usefulness” of routes nearby, such as distance to the nearest stop, frequency, and type. Unlike the bike score, they don’t take into consideration riders’ satisfaction or effectiveness of the transit.
It’s hard to argue with Walk Score’s main conclusions on the benefits of walkability: residents average 6-10 pounds lighter in a walkable neighborhood, property values can be $600-$3,000 higher with each Walk Score point (and reduce the second largest household expense, your car), as well as the study that for every 10 minutes spent in a daily car commute, time spent in community activities falls by 10%. You can now even search hotels by proximity and travel time to the locations you’re planning on visiting.
Walk Score data is even being used now in urban planning using such metrics as average block length and intersection density. This is probably an improvement considering that the Project for Public Spaces calculated the Walkscore for every state’s Department of Transportation headquarters, and came up with an average 67 on a scale of 0-100. See the PDF list here.
Another clever use of data is the City of Hoboken, NJ, announcing a combined bike rental-and-sharing program that will greatly reduce costs of operating the system. Social Bicycles puts a lock and GPS on the bike so it can be locked to traditional bike racks and while serving to track where bikes travel at what time, thus gathering large amounts of data data to help guide investments in improving effectiveness and safety of the system. Now they just need an integrated payment system like the transit pass proposed in Sao Paulo’s 150,000 bike-sharing system.
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Spotlighting innovations in urban sustainability and connected technology
A study by the US National Center for Atmospheric Research (NCAR) in 2008 found that the impact of routine weather events on the US economy equates annually to about 3.4% of the country’s GDP (about $485 billion). This excludes the impact of extreme weather events that cause damage and disruption – after all, even “ordinary” weather affects supply of and demand for many items, and the propensity of businesses and consumers to buy them. NCAR found that mining and agriculture are particularly sensitive to weather influences, with utilities and retail not far behind.
Many of these, disaster management included, are the focus of smart city innovations. Not surprisingly, therefore, as they seek to improve and optimize these systems, smart cities are beginning to understand the connection between weather and many of their goals. A number of vendors (for example, IBM, Schneider Electric, and others) now offer weather data-driven services focused specifically on smart city interests.
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