1	IntelliDrive^SM Data Capture and Management Program
2	Outline Program Vision and Objectives Key Concepts Current Projects and Products Upcoming Activities Issues Question and Answer
3	IntelliDriveMobility
4	Real-Time Data Capture and Management Vision Active acquisition and systematic provision of integrated, multi-source data to enhance current operational practices and transform future surface transportation systems management Objectives Enable systematic data capture from connected vehicles (automobiles, transit, trucks), mobile devices, and infrastructure Develop data environments that enable integration of data from multiple sources for use in transportation management and performance measurement Reduce costs of data management and eliminate technical and institutional barriers to the capture, management, and sharing of data
5	Data Environment Concept Data environment: well-organized collection of data of specific type and quality captured and stored at regular intervals from one or more sources systematically shared in support of one or more applications
6	Key Issues in Defining A Data Environment
7	Data Sources and Uses
8	Data Aggregation and Structure
9	Data Environment Evolution
10	Elements of Data Capture and Management Meta data: Provision of well-documented data environment Virtual warehousing: Supports access to data environment and forum for collaboration History/context: Objectives of data assembly Governance: Rules under which data environment can be accessed and procedures for resolving disputes
11	Each Data Environment Supports Multiple Apps Overlapping data needs and synergy between application concepts
12	Federated Data Environments
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14	Projected Program Outcomes Establish a system of IntelliDrive federated data environments Broad collaboration supporting data environment utilization Leverage data to support high-priority application development Encourage technical exchange between researchers Implementation of data management processes representing best practices
15	Current Projects and Program Products Current Projects Technical State-of-the-Practice/Innovation Scan USDOT Lead: Mohammed Yousuf (FHWA R&D) Principal Investigator: Dick Mudge (Delcan) Policy Assessment* USDOT Lead: Walter During (FHWA Office of Operations) Lead Researcher: Suzanne Sloan (Volpe Center) Standards Assessment* USDOT Lead: Tom Stout (FHWA) Principal Investigator: Nu Rosenbohm (SAIC) Data Environment Evaluation Framework USDOT Lead: Walter During (FHWA) Principal Investigator: Anita Vandervalk (Cambridge Systematics) Available Program Products Program vision, other documents on IntelliDrive website Prototype Data Environment
16	Data Capture Prototype Data Environment https://datacapture.noblis.org/ Data (and meta-data) from the Michigan IntelliDrive Test Bed Documented probe data samples from recent tests (POC/NCAR) Open source analytical tools Simulated 100% market penetration data for the test bed contributed by the University of Michigan Transportation Research Institute (UMTRI) Forums for researchers to register projects, flag erroneous data, contribute analyses and data views Prototype objectives Refine the Data Environment concept Test key hypotheses about governance and user collaboration
17	Log Files from Onboard Equipment (OBE)
18	Snapshots Collected by Roadside Equipment (RSE)
19	Trajectory Conversion Analysis (TCA) Program Open Source Python program Inputs Vehicle Trajectory Files (Actual or Simulated) RSE locations and range Parameters for snapshot generation & transmission Outputs Snapshots generated and transmitted to RSEs Snapshots discarded for buffer overflow or RSE gap Probe segment number changes
20	UMTRI Paramics Simulation of the Testbed 189 Origin/Destinations Models 6 AM – 11 AM 10,000 concurrent vehicles RSE interactions modeled
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22	Upcoming Activities Precise nature, extent and timing are not yet known, however, the program expects to procure assistance in the following areas: Test Data Sets Assemble already collected data sets featuring multi-source data collected using emerging technologies Supports early application research Data Environment Development Develop and make available data environments supporting high-priority applications research and development Federated System Data Manager Connect, foster and manage system of federated data environments
23	Key Issues Intellectual property rights Privacy Governance Standards and Regulation Meta-Data Quality Assurance Storage Access and Security Operations and Maintenance
24	Questions? Thank you