Research Overview

Real-Time Data Capture and Management is the creation and expansion of access to high-quality, real-time and archived, multi-modal transportation data that is captured from connected vehicles (automobiles, buses, trucks, fleets), mobile devices, and infrastructure.

The vision for the Real-Time Data Capture and Management research is the active acquisition and systematic provision of integrated, multi-source data to enhance current operational practices and transform future surface transportation systems management.

Research Goals

The goals of the Real-Time Data Capture and Management research program are to:

• Systematically capture real-time, multi-modal data from connected vehicles, devices, and infrastructure.
• Develop data environments that enable integration of high-quality data from multiple sources for transportation management and performance measures.

Research Questions

The Real-Time Data Capture and Management research program explores the following questions:

• What data is available today from both traditional and non-traditional sources? What is the quality?
• How can probe data be integrated with traditional data sources to support traffic, transit, and freight applications?

Research Approach

Overview

The objective of the Real-Time Data Capture and Management research program is to enable the development of environments that support the collection, management, integration, and application of real-time transportation data or data sets.

Real-time data applications offer an ability to increase safety and operational efficiency nationwide. Not only will this data allow travelers to make better informed travel decisions, but public- and private-sector data on all modes and roads can be used to transform transportation management. Real-time data also have the potential to support a range of multi-modal mobility applications. Real-time information on parking availability and transit schedules can enable smarter mode choice decisions and efficiencies for travelers. Updated freight movement data assists commercial freight operators with optimizing operations. Overall, the information developed from the Real-Time Data Capture and Management research program will reveal opportunities for achieving greater efficiencies within our transportation systems.

Some types of data that can be captured and managed include: situational safety, environmental conditions, congestion data, and cost information derived from both traditional (traffic management centers, automated vehicle location systems) and non-traditional (mobile devices, connected vehicle equipment) sources. Data can also be collected from sources that generate data on elements of the transportation system such as toll facilities, parking facilities, and transit stations.

Results that are key to success in this research area include:

• Establishment of one or more multi-source data environments for the development and testing of safety, mobility, and environment applications.
• Engagement of stakeholders to assist in defining the requirements for test data environments and to encourage active use of prototypes and test beds.
• Identification of data management processes, operational practices, standards, integration, and rules for data exchange and sharing, particularly across jurisdictions.
• Successful testing that validates assumptions about:
• Data (availability and accessibility of sources, quality, reliability, consistency, timing, etc.).
• Management and operational practices (how real-time data capture and use are managed).
• Benefits, as they are demonstrated through testing of the applications.

Success will be further measured by progress on:

• Synthesis of foundational research to assess the state of the industry.
• Development of a variety of large-scale data sets (utilizing connected vehicles, mobile devices, and infrastructure) for testing transportation management and performance measurement applications.
• Demonstrations of multi-modal and multi-state, real-time data capture and management to show the value of ubiquitous transportation information.

Program Tracks

The ITS Program will use a collaborative, multi-track approach to comprehensively address the Real-Time Data Capture and Management research needs:

• Track 1: Engage stakeholders for input from initial analysis to pilot deployment. Test data sets, data collection, and analysis methodologies will be shared with stakeholders, with information made available to the broader transportation community.
• Track 2: Develop data environments to support transportation applications and address technical, institutional, and standards issues surrounding the collection and dissemination of data.
• Track 3: Conduct proof-of-concept tests, and test standards, procedures, tools, and protocols to provide implementation guidance for real-world deployment.
• Track 4: Conduct pilot deployments and demonstrate the data capture and data management techniques in an operational setting, while providing stakeholders with opportunities to develop systems that will extend beyond the life of the program.
• Track 5: Develop evaluation and performance measures to assess benefits of the data environments.
• Track 6: Share the program’s findings and procedures with stakeholders and the broader transportation community through coordinated outreach activities and technology transfer.

This research program will build on the existing Real-Time Information Market Assessment and the recent Real-Time System Management Information Program. Collaboration is expected from a wide range of stakeholders to help guide the research program. Related U.S. DOT research programs, such as Dynamic Mobility Applications (DMA) and Applications for the Environment: Real-Time Information Synthesis (AERIS), are anticipated both to define data requirements (and identify information gaps) as well as to use real-time data sets that are developed under this program.

Research Outcomes

The results of this research program will be used to develop additional data environments and demonstrations that show the value of widespread real-time, multi-modal information.

Real-time data can be integrated across modes and made available to users.

Data sharing between modes can be used to improve operational efficiencies to transform surface transportation management.

Multi-modal data sets have the potential to support a range of mobility applications for real-time information sharing.

Resources

• Real-Time Data Capture and Management Evaluation and Performance Measures Evaluation Framework
• Real-Time Data Capture and Management Fact Sheet [PDF 669KB]
• Data Capture and Management Program Vision: Objectives, Core Concepts and Projected Outcomes
• Data Capture and Management Program: High Level Roadmap Chart
• Data Capture and Management Program: Transforming the Federal Role
• Transportation Research Board Annual Meeting Presentations, January 26, 2011
  • Moving Towards Implementation of Wireless Connectivity in Surface Transportation [PDF 886KB]
  • USDOT Perspective on Data Collection, Aggregation and Distribution [PDF 427KB]
• Vehicle-Infrastructure Integration (VII) Probe Data Characteristics: Analyses of Three Field Data Sets (Jun 2007)
• VII Data Characteristics for Traffic Management and Traveler Information Strawman Measures Explanation Memo (Jul 2006) [PDF 57KB]
• VII Data Characteristics Task: Data Needs Assessment (Jun 2006) [PDF 287KB]
• Research Plan for a Transportation Industry Paradigm Shift: The Impact of New Measures Produced by the VII Program (Jul 2004) [PDF 125KB]

Research Contacts

To learn more about this research, contact:

Dale Thompson
Transportation Research Specialist
ITS Joint Program Office
Research and Innovative Technology Administration
(202) 493-0259
dale.thompson@dot.gov

Gene McHale
Team Leader, Transportation Enabling Technologies
Office of Mobility Innovation
Federal Transit Administration
(202) 493-3275
gene.mchale@dot.gov

Randy Butler
Freight Technology Manager
Office of Freight Management and Operations
Federal Highway Administration
(202) 366-9215
randy.butler@dot.gov