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There is a new approach to collaboration in motion in the field of active transportation planning: one that harnesses many of the quickly evolving technologies changing how planners collect information and communicate. It s called "crowdsourcing," which can be described as the process of obtaining information, insight, and knowledge from user-generated data provided through web and mobile applications. Crowdsourcing has already taken many different forms and served a wide variety of transportation planning purposes, from identifying new bike share station locations and collecting personal travel data using GPS to mining data from personal fitness apps for travel patterns.1,2,3 Access to high-quality data in greater quantities and at finer spatial resolutions, as well as new capabilities for direct communication with community members, offers important new options for listening to bicyclists and pedestrians and working with them to better understand their relationships with the built environment, their travel decisions, and their needs.
While planning professionals have certainly been making waves with innovative approaches to data collection and civic engagement through crowdsourcing, the broad reach of technologies that make crowdsourcing possible, such as GPS-enabled mobile devices, also help professionals and non-professionals alike to collaborate and share knowledge in real time. New capabilities for GPS, mobile devices, and intelligent transportation systems (ITS) are even inspiring some communities to think about developing live, demand-responsive crowdsourcing applications, such as a system being developed by the City of Austin, TX, USA that detects cyclists carrying smartphones and is able to adjust signal timing "on the fly."4 These types of crowdsourcing efforts and applications increasingly tap into big data, using large, multifaceted data sources and aggregation methods to examine trends and in turn to help users make travel decisions.5 Advances in computer science, such as machine learning, add to the mix. Using a combination of crowdsourced survey responses and image processing techniques applied to Google Streetview images, researchers at Massachusetts Institute of Technology (MIT) are studying the visual qualities of urban environments that tend to be perceived as safe or unsafe. This could help urban planners assess how the built environment affects travel behavior decisions in a much more nuanced way.6
With all of these success stories, research innovations, and ideas making waves, it's easy to get caught up in the excitement that...