Within these pages, readers will find information related to the integration and management of crowdsourced data. Crowdsourced data include active data generated through the use of social media apps (e.g., Waze, Twitter), as well as passive data collected via cell phones (e.g., probe speed data, traveler behavior), transponders (e.g., E-ZPass, freight), and vehicle systems (heavy breaking, wiper on/off, CVs). Crowdsourced data have tremendous potential to offer new insights; however, the volume and speed at which these data are generated are unprecedented. To handle these “big data,” modern, flexible, and scalable methods to manage these data must be adopted by transportation agencies if the data will be used to facilitate better decision-making.
Currently, the most common applications of crowdsourced data are traveler information and incident management; however, agencies are expanding use in areas such as traffic signal timing, maintenance, road weather, and work zone management. The major barriers for agencies seeking to more effectively use crowdsourced data include understanding and assessing the quality of the data, storing and managing the large amount of data, and turning the data into information to support operational decision-making. In some cases, agencies struggle to make the business case for purchasing or using the data because management does not fully understand the potential benefits of the data.
08-119 Research Product: