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IntelliDriveSM Connectivity − Mobility

ITS America WebconferenceUSDOT Overview for the Private Sector Transportation Data Community

Ben McKeever, Gene McHale, Bob RupertFHWA

13 September 2010

IntelliDrive is a service mark of the U.S. Department of Transportation.

What is IntelliDriveSM?

• IntelliDriveSM is a suite of technologies and applications that use wireless communications to provide connectivity:– Among vehicles of all types– Between vehicles and

roadway infrastructure– Among vehicles,

infrastructure and wireless consumer devices

Vehicles

WirelessDevices

Infrastructure

Drivers

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IntelliDrive Program Structure

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Evolution of IntelliDrive DeploymentOriginal VII Deployment Model

DSRC based for all applications▪ Infrastructure intensive using new DSRC technology▪ Vehicle turnover for embedded DSRC technology

Start with V2I (for all application types) and evolve into V2V (safety)

US DOT’s Current Perspective on IntelliDrive Deployment Non-safety (mobility, environment)

▪ Leverage existing data sources & communications; include DSRC as it becomes available

▪ Support development of key applications for public agencies using current data sources and evolving probe data from IntelliDrive

Safety DSRC▪ Aggressively pursue V2V; leverage vehicle capability for V2I spot safety▪ Can leveraging of nomadic devices & retrofitting accelerate benefits?▪ Infrastructure requirement for security is still a TBD

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IntelliDriveSM Mobility

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Data Environment

Real-time Data Capture and ManagementMobility and Environmental

Applications

Transit Data

Truck Data

Reduce Speed 35 MPH

Weather Application

Transit Signal Priority

Fleet Management/

Dynamic Route Guidance

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

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Creating a Data Environment

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

Data Environment

Application

Data Capture

Information

Raw Data

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What Data Do We

Capture?

How Do We Use

The Data?

What Data Do We Keep?

How Do We Structure The Data?

How Do We Structure The Data?Key Issues in Defining A

Data Environment

Data Sources and Uses

SOURCES

USES

SOURCES USES

MOBILITY SAFETYENVIR.TRANSIT FREIGHTLIGHT VEHICLE

LOOP RADAR OTHER

VEHICLE

INFRASTRUCTURE

LOCATION DECISIONS

TRAVELERPERFORMANCEMEASUREMENT

TRAVELERINFORMATION

VARIABLESPEED LIMITS

OTHER

OTHEROTHER

ECO-DRIVE

QUEUEWARNING

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STRUCTURE

Data Aggregationand Structure

STRUCTURE

AGGREGATION

AGGREGATION

AREA-WIDEAGGREGATION

RAWDATA

QUALITY

IP

PRIVACY

ACCESS

STANDARDS

REGULATION

STORAGE

AGGREGATION

STRUCTURE

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Potential End StateCurrent State

Potential Interim States

T

V

IT

V

I

T

V

I

Data Environment Evolution

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TRAVELER

VEHICLE

INFRASTRUCTURE

“some”

“a few”

“nearly zero”

VEHICLE

TRAVELER

“nearly all”

“some”

“where needed”

INFRASTRUCTURE

GOVERNANCE

HISTORY/CONTEXT

VIRTUAL WAREHOUSING

Application

META-DATA

Capture

InformationRaw Data

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

Data Environment

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Projected Outcomes

• Establish one or more data environments• Broad collaboration supporting data environment utilization• Implementation of data management processes representing best

practices

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Dynamic Mobility Applications

Vision• Expedite development, testing, commercialization, and deployment of innovative

mobility applications:– maximize system productivity– enhance mobility of individuals within the system

Objectives• Create applications using frequently collected and rapidly disseminated multi-

source data from connected travelers, vehicles (automobiles, transit, freight) and infrastructure

• Develop and assess applications showing potential to improve nature, accuracy, precision and/or speed of dynamic decision making by system managers and system users

• Demonstrate promising applications predicted to significantly improve capability of transportation system to provide safe, reliable, and secure movement of goods and people

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Guiding Principles

• Leverage multi-source data• Develop and test mode-specific and multi-modal applications• Feature open source application research and development• Encourage competitive application commercialization• Prioritize program resources based on expected impact• Enhance analytical capabilities related to mobility applications• Practice long-term technology stewardship

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Leverage Multi-Source Data

• Leverage high-quality data integrated from mobile and fixed sources to develop multiple applications (mode-specific and multi-modal)

• Requires coordination with Real-Time Data Capture and Management program

DATAENVIRONMENT

MODE-SPECIFICAPPLICATIONS

(e.g., for freight vehicles)

a

b

c

VEHICLES

TRAVELERSINFRASTRUCTURE

TRANSIT

FREIGHTLIGHT VEHICLE

MULTI-MODALAPPLICATIONS

(e.g., for travelers)

CROSS-MODALAPPLICATIONS

(e.g., for system managers)

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Multi-Modal Applications Development and Test

• Coordinated development of mode-specific and multi-modal applications:– avoid duplication– cost-effective

a

b

cDATA

ENVIRONMENT

VEHICLES

INFRASTRUCTURE

TRAVELERS TRAVELERS

MANAGERS

FLEET OPERATORS

APPLICATIONS

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Open Source Research and Development

• Research issue is too complex or big for isolated researchers to solve• Promotes highest level of collaboration• Preserves intellectual capital• Serves to engage partners from academia and industry who may not be

directly involved in funded applications development and testing

• Currently seeking to refine how best to structure open source agreements– maximize collaboration– without reducing innovation or endangering commercialization

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Encourage competitive application commercialization

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APPLICATION DEPLOYMENT LIFE-CYCLE

RESEARCH DEVELOPMENT COMMERCIALIZATION SUPPORT

PRIVATESECTORFOCUS

PUBLICSECTORFOCUS

COMPETITIVEAPPLICATION

COMMERCIALIZATION

COOPERATIVERESEARCH

ANDDEVELOPMENT

OPEN

DATA

OPEN

SOU

RCE

DEVELOPM

ENT

TECHNO

LOGY

TRANSFER

Prioritize resources based on expected impact

• Develop prototype mobility application that focuses on performance measures:– exploits new or integrated data sources– enhances traditional measures or creates new measures to capture

full impact of mobility applications• Prioritization of development and test of candidate applications:

– applications must improve system productivity or user mobility– well-defined, quantitative performance measures (multi-modal or

mode independent)– applications must have broad stakeholder interest and support

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Enhance analytical capabilities

• Develop analytic tools and processes to accurately predict impacts:– assess long-term performance– use real-time prediction to support improved decision making by

travelers, system managers and other transportation system stakeholders (e.g., fleet operators)

• Employ tools to refine and identify promising applications prior to committing resources for field testing or full demonstration

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Practice long-term technology stewardship

SIGNAL RETIMING

SIGNAL RETIMING

PREDICTIVE VMS

SPEED HARMONIZATION

A

B

A

SIGNAL RETIMING

PREDICTIVE VMSB

A

C

“few probes, some sensors”

“some probes, some behavioral data, some sensors”

“most vehicles are probes, more behavioral data, some sensors”

I

II

III

DATAENV.

DATAENVIRONMENT

DATAENVIRONMENT

DA

TA

EN

VIR

ON

ME

NT

+ AP

PLIC

AT

ION

S E

VO

LUT

ION

SIGNAL RETIMING

SIGNAL RETIMING

PREDICTIVE VMS

SPEED HARMONIZATION

A

B

A

SIGNAL RETIMING

PREDICTIVE VMSB

A

C

“few probes, some sensors”

“some probes, some behavioral data, some sensors”

“most vehicles are probes, more behavioral data, some sensors”

I

II

III

DATAENV.

DATAENVIRONMENT

DATAENVIRONMENT

DA

TA

EN

VIR

ON

ME

NT

+ AP

PLIC

AT

ION

S E

VO

LUT

ION

DA

TA

EN

VIR

ON

ME

NT

+ AP

PLIC

AT

ION

S E

VO

LUT

ION

DA

TA

EN

VIR

ON

ME

NT

+ AP

PLIC

AT

ION

S E

VO

LUT

ION

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Projected Outcomes

• Multiple applications developed leveraging multi-source data• Research spurs commercialization• Applications enable transformational change

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Keys to Success for IntelliDrive Mobility

• Facilitate easy, secure access to data environment and enable collaboration in mobility application development

• Accumulate and share intellectual capital while respecting IP rights• Coordination with other IntelliDrive program areas and broader ITS

programs• Active interaction with broader group of stakeholders outside the federal

research and development efforts• Not a one-time engagement, will require ongoing collaboration to:

– refine program goals– refine data needs– structure relevant and feasible data environment development efforts– prioritize applications development and testing

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Getting Involved

• Provide feedback on program direction, goals, data environment, mobility applications

• Respond to upcoming funded requests for research and development of mobility applications

• Seek to leverage IntelliDrive data and applications resources in other non-federal or non-IntelliDrive federally funded research projects

• Offer new data sets and applications• Actively commercialize mobility applications developed within the

IntelliDrive program

• Utilize the IntelliDrive Prototype Data Environment• Submit application concepts using the Candidate Applications Template

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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)

• Trajectory Conversion Analysis (TCA) program

• 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

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Data Capture and Mngmt Future Activities

• Investigations into state-of-the-practice for technologies, institutional and policy, and standards

• Broad Agency Announcement (BAA) for Test Data Sets• Acquisition and hosting of IntelliDrive funded data, such as

– Near term performance measures demo– Safety Pilot– Mobility Application Demos– IntelliDrive Test Bed

• Development of data environments to support Mobility applications

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Candidate Mobility Applications Concepts

Goal• Identify, with help of stakeholders, collection of applications for development and testing in

Phase 2 of ProgramApproach• Solicit ideas for transformative applications that improve decision making by system

managers and users– Template available for submission of ideas at:

http://www.its.dot.gov/intellidrive/app_template/DMA_template.htm – Initial request closed on 31 July; second call issued (closes 15 October)– 46 submittals with 49 application ideas (as of 31 August)

• Combine suggested applications of interest to condensed list to avoid duplication• Prioritize condensed list for future development and testing

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Mobility Applications Template

Contributor types:• Academia: 7• State/local government: 14• Private sector: 10• Federal government: 5• Non-government organization:

4• VII Day One: 6

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Types of Applications:• Traffic Control: 4• Traveler Information: 11• Active Traffic Management: 11• Transit-related: 10• Freight-related: 7• Rural: 4• Pedestrians/Bicycles: 2• Weather-related: 4• Other / unrelated: 9

Summary of Submittals to Date (46 received)

Summary report available at:http://www.its.dot.gov/intellidrive/app_template/DMAcandidateAppsSummaryAug.htm

Submitting New Concepts

• Got a transformative idea that utilizes IntelliDrive data?– Fill out template online:

http://www.its.dot.gov/intellidrive/app_template/DMA_template.htm

– Or, fill out a template off-line and send it via e-mail

• Template requires high-level description of idea– Problem being addressed– Transformative benefits– How the idea makes use of IntelliDrive data

• Deadline for getting your idea in: 15 October 2010

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Near-Term Performance Measurement Demonstration

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• Goal: – In CY 2011, potentially initiate one or more field demonstrations – Utilize IntelliDrive data from probe vehicles, mobile devices and

infrastructure sensors – Measure and characterize overall transportation system productivity

(not just facility or mode) and individual mobility (across modes)

• Proposed Elements– Multi-source data capture and integration (vehicles, rail, freight,

travelers) to support innovation in performance measurement– Critical mass demonstration in a complex (multi-modal) system– Share data from demonstration through Data Capture program

For More Information…

http://www.intellidrive.org/

Contact Information

• Ben McKeever, FHWA– ben.mckeever@dot.gov

• Gene McHale, FHWA– gene.mchale@dot.gov

• Bob Rupert, FHWA– robert.rupert@dot.gov

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