The expanding deployment of emerging transportation technologies, including connected vehicles (CVs), automated vehicles (AVs), shared mobility, mobility on demand, and activities associated with smart cities and communities, has increased the need and demand for improved management of associated data. While existing transportation databases have sometimes been curated and analyzed for specific project purposes, improved collaboration is needed to inform state and local agencies of lessons learned and best practices, which often produce ”big data” at magnitudes not previously seen.
To demonstrate and build on these emerging technologies, a wide range of institutions, both public and private, have initiated and invested in major pilot programs. These efforts are also supported by U.S. DOT through several federal initiatives such as the following:
· CV Pilot Deployment Program,
· The Smart City Challenge,
· The Advanced Transportation and Congestion Management Technologies Deployment Program of FHWA
As these efforts continue to expand, the amount and quality of data surrounding the application of emerging technologies is also expanding. In response, an improved collaborative approach to data analytics has the potential to improve our ability to address transportation planning and policy questions critical to informed and effective decision-making at state and local public agencies.
State and local transportation agencies are eager to learn from the experiences of early adopters of changing and emerging transportation technologies. Formulating a framework that establishes specific procedures for identifying, collecting, aggregating, analyzing, and disseminating data should significantly contribute to effective transportation decision-making.
The objectives of this research were the following:
1. To develop a framework for identifying, collecting, aggregating, analyzing, and disseminating data from emerging public and private transportation technologies.
2. To outline a process for using this framework to help decision-makers incorporate data from emerging technologies into transportation planning and policy.
1. Review the state-of-the-practice at state and local levels for identifying, collecting, aggregating, analyzing, and disseminating data from emerging public and private transportation technologies. This task will include an extensive literature review.
2. Synthesize the kinds of data being collected, and, based on this synthesis, establish a taxonomy of procedures and supporting metrics for identifying, collecting, aggregating, analyzing, and disseminating data. At a minimum, consider the following questions:
a. How are the data being used?
b. What are the objectives for collection and use of the data?
c. What data curation models are currently in use?
d. What are the commonalities and differences among different practices?
e. What data governance practices are in use?
f. What lessons can be drawn from current experience?
3. Building on the review of the state-of-the-practice, including an analysis of overall data requirements and recognized gaps, develop the framework to include step-by-step procedures and supporting metrics for identifying, collecting, aggregating, analyzing, and disseminating data from emerging public and private transportation technologies. In each step, specify possible data providers, users, and other stakeholders. Document facilitators, barriers, and the potential means to overcome the barriers for implementing the steps. In addition, the framework should include potential procedures for implementing open data policies.
4. To facilitate implementation of the research results, demonstrate how the developed framework can be applied, and make recommendations for procedural changes in identifying, collecting, aggregating, analyzing, and disseminating data from emerging public and private transportation technologies.
5. Prepare appropriate documentation, including a detailed guidebook, for use by analysts and decision-makers in implementing the proposed data collection and application framework. Documentation may include visual representations and other graphical techniques to enhance receptivity by the intended audiences.
Status: The final report is now available, Report 952 along with additional supporting materials and documentation..