The presentation provided an overview of the US Department of Transportation's Connected Vehicles Deployment Program and a deeper dive into the Tampa Connected Vehicle pilot. It discussed the goals of the pilot program, the three pilot sites including details about the Tampa pilot, the connected vehicle applications being deployed, and the evaluation approaches and performance measures being used to assess the pilots. It also covered challenges and lessons learned regarding program management, performance measurement, and systems engineering for the connected vehicle deployments.
Science 7 - LAND and SEA BREEZE and its Characteristics
DOT Connected Vehicle Deployment Program Overview
1. U.S. Department of Transportation
Presenter: Govindarajan Vadakpat, Research Transportation Specialist, FHWA
2. 2U.S. Department of Transportation
WHAT TO EXPECT IN THIS SESSION
Overview of the Connected Vehicles Deployment Program
Deeper dive into the THEA CV pilot
Other Deployment Opportunities at FHWA
Avenues for Research Opportunities at FHWA
NYCDOT WYDOT USDOTTampa (THEA)
4. 4U.S. Department of Transportation
THE THREE PILOT SITES
Reduce the number and severity of adverse weather-related incidents in the I-
80 Corridor in order to improve safety and reduce incident-related delays.
Focused on the needs of commercial vehicle operators in the State of Wyoming.
Alleviate congestion and improve safety during morning commuting hours.
Deploy a variety of connected vehicle technologies on and in the vicinity of
reversible express lanes and three major arterials in downtown Tampa to solve
the transportation challenges.
Improve safety and mobility of travelers in New York City through connected
vehicle technologies.
Vehicle to vehicle (V2V) technology installed in up to 8,000 vehicles in Midtown
Manhattan, and vehicle to infrastructure (V2I) technology installed along high-
accident rate arterials in Manhattan and Central Brooklyn.
Wyoming DOT
New York City DOT
6. 6U.S. Department of Transportation
Connected Vehicle Communication
6
Vehicles have
360 degree
awareness of
surroundings
Communicate
with other
vehicles 10 times
per second
“Basic Safety
Messages”
13. 13U.S. Department of Transportation
PARTICIPANTS
10
Hillsborough Area
Regional Transit
(HART) buses
1,600
Privately Owned
Vehicles
PHOTO: THEA
500+
Pedestrian
Smartphones
(Android devices only)
PHOTO: NPR
10
TECO Line
Streetcar Trolleys
PHOTO: THEA PHOTO: THEA
14. 14U.S. Department of Transportation
MORNING BACKUPS
Forward Collision
Warning (FCW)
Emergency
Electronic Brake
Light (EEBL)
End of Ramp
Deceleration
Warning (ERDW)
Intelligent Signal
Systems (I-SIG)
PHOTO: TAMPA HILLSBOROUGH EXPRESSWAY AUTHORITY
(THEA)
15. 15U.S. Department of Transportation
WRONG-WAY DRIVERS
Wrong-way
Entry
Intersection
Movement
Assist (IMA)
MAP
Signal Phasing
and Timing
(SPaT)
PHOTO: TAMPA HILLSBOROUGH EXPRESSWAY AUTHORITY
(THEA)
16. 16U.S. Department of Transportation
WWE: What the OBU “Sees”
Source: Siemens Industry Inc.
Morning
Afternoon
17. 17U.S. Department of Transportation
PEDESTRIAN SAFETY
PHOTO: TAMPA HILLSBOROUGH EXPRESSWAY AUTHORITY
(THEA)
Pedestrian in a
Signalize
Crosswalk
Warning (Ped-X)
Pedestrian
Collision Warning
(PCW)
18. 18U.S. Department of Transportation
PCW: What the OBU “Sees”
Source: Mentor, a Siemens Business
Source: Siemens Industry Inc.
No False Positives
No False Negatives
CUTR: Lidar vs. PSD location service
Use for PTMW Geo Fence settings
19. 19U.S. Department of Transportation
TRANSIT SIGNAL PRIORITY
PHOTO: TAMPA HILLSBOROUGH EXPRESSWAY AUTHORITY
(THEA)
I-SIG
Transit Signal
Priority (TSP)
IMA
Pedestrian
Transit
Movement
Warning
(PTMW)
20. 20U.S. Department of Transportation
STREETCAR CONFLICTS
PHOTO: TAMPA HILLSBOROUGH EXPRESSWAY AUTHORITY
(THEA)
Vehicle Turning
Right in Front of
Transit Vehicle
(VTRFTV)
PTMW
21. 21U.S. Department of Transportation
TRAFFIC PROGRESSION
PHOTO: TAMPA HILLSBOROUGH EXPRESSWAY AUTHORITY
(THEA)
Probe Data
Enabled Traffic
Monitoring
(PDETM)
Pedestrian
Mobility (PED-SIG)
I-SIG
IMA
24. 24U.S. Department of TransportationAA
Mirror display uses sticker to depict location and concept of warning.
Actual image is still in development
Source: Brand Motion and Global 5
HMI PHOTOS
25. 25U.S. Department of Transportation
METRICS IDENTIFIED PMESP
6 Use Cases
11 CV Apps
40 RSUs
4 Evaluation “Pillars”
□ Mobility
□ Environmental
□ Safety
□ Agency Efficiency
3 Experimental
Designs
22 Potential
Measures
Performance
Pillars
Performance Measures
UC1 Morning
Peak Hour
Queues
UC2
Wrong
Way
Entries
UC3
Pedestrian
Safety
UC4
BRT
Signal
Priority
UC5
Trolley
Conflicts
UC6
Enhanced
Signal
Coordination
Progression
Travel time
Travel time reliability
Queue length
Vehicle delay
Throughput
Percent (%) arrival on green
Bus travel time
Bus route travel time reliability
Percent (%) arrival on schedule
Signal priority: -
Number of times priority is
requested and granted
- Number of times priority is
requested and denied
- Number of times priority is
requested, granted and then
denied due to a higher priority
(i.e. EMS vehicle)
Emissions reductions in idle
Emissions reductions in running
Mobility
Environmental
26. 26U.S. Department of Transportation
METRICS IDENTIFIED PMESP (CONTINUED)
6 Use Cases
11 CV Apps
40 RSUs
4 Evaluation “Pillars”
□ Mobility
□ Environmental
□ Safety
□ Agency Efficiency
3 Experimental
Designs
22 Potential
Measures
Performance
Pillars
Performance Measures
UC1 Morning
Peak Hour
Queues
UC2
Wrong
Way
Entries
UC3
Pedestrian
Safety
UC4
BRT
Signal
Priority
UC5
Trolley
Conflicts
UC6
Enhanced
Signal
Coordination
Progression
Crash reduction
Crash rate
Type of conflicts / near misses
Severity of conflicts / near misses
Percent (%) red light
violation/running
Approaching vehicle speed
Number of wrong way entries
and frequency
Mobility improvements through
the mobility pillar analysis
Safety improvements through the
safety pillar analysis
Customer satisfaction through
opinion survey and/or CV app
feedback
Agency
Efficiency
Safety
27. 27U.S. Department of Transportation
EVALUATION APPROACHES
Random Design – Treatment and Control groups, random assignment,
compare average treatment effect, desirable but always achievable
Quasi-Experimental – Used when random assignment not possible,
selection bias reduced by using methods like propensity score
matching, matching algorithm, difference in difference
Before/After – Time series analysis, no control and treatment groups,
confounding factor identification, baseline data required
28. 28U.S. Department of Transportation
DEPLOYMENT STATUS AND NEXT STEPS
SOURCE: HNTB
29. 29U.S. Department of Transportation
PROGRAM MANAGEMENT
– CHALLENGES / LESSONS LEARNED
Challenges
1. Distributed Team Locations – Logistics
2. Aggressive Delivery Schedules
3. Balancing High Energy, Super Talented Teams with Need to have Centralized PM
4. HIGH Number of Stakeholders with Initially Low Level of Comprehension
Lessons Learned
1. Importance of face to face progress meetings followed by breakout sessions
2. Critical documents have overlapping/redundant content.
a) Each progressive document must be reconciled with prior documents
b) QC/QA should include dedicated staff having no other project involvement
c) Reconciliation document for tracking these connected changes
3. Balance needed between empowering team leads to operate autonomously and maintaining
centralized program management to keep all teams informed and connected
4. Need to not only engage early but to educate early as to the “Benefits” of the program and why
their participation is key to success.
30. 30U.S. Department of Transportation
PERFORMANCE MEASUREMENT & EVALUATION
– CHALLENGES/ LESSONS LEARNED
Challenges
1.Deployment in an area undergoing significant redevelopment will likely complicate
dealing with confounding factors
2.Identification of performance targets more difficult than developing measures and
methods.
Lessons Learned
1.Cross functional coordination is absolutely critical
2.Early involvement in activities such as System Requirements helps facilitate
meaningful measurement
3.Early definition of needs and role of Independent Evaluator would be helpful
31. 31U.S. Department of Transportation
SYSTEMS ENGINEERING
– CHALLENGES / LESSONS LEARNED
Application maturity not as evolved as expected
Evolving standards
Concurrent planning documents development
More direct interaction with other teams
Use of non-CV technology as part of solution
Security
32. 32U.S. Department of Transportation
STAY CONNECTED
Contact for CV Pilots Program/Site AORs:
Kate Hartman, Program Manager, Wyoming DOT Site AOR; Kate.Hartman@dot.gov
Jonathan Walker, NYCDOT Site AOR; Jonathan.b.Walker@dot.gov
Govind Vadakpat, Tampa (THEA) Site AOR; G.Vadakpat@dot.gov
Visit CV Pilot and Pilot Site Websites for More Information:
CV Pilots Program: http://www.its.dot.gov/pilots
NYCDOT Pilot: https://www.cvp.nyc/
Tampa (THEA): https://www.tampacvpilot.com/
Wyoming DOT: https://wydotcvp.wyoroad.info/ NYCDOT WYDOTTampa (THEA)
33. 33U.S. Department of Transportation
ADVANCED TRANSPORTATION
AND CONGESTION MANAGEMENT
TECHNOLOGIES DEPLOYMENT
GRANT (ATCMTD)
33
DEPLOYMENT OPPORTUNITIES
34. 34U.S. Department of Transportation
ATCMTD Awards in 2016 & 2017
2016 - applications received from ~90 entities.
8 projects were selected for award.
2017 - applications received from ~70 entities.
10 projects were selected for award.
https://ops.fhwa.dot.gov/fastact/index.htm
37. 37U.S. Department of Transportation
37
Key Processes
Focus on high-risk, high payoff research
Merit review is used to enhance the quality of research processes
and results
Research stakeholders are involved throughout
Commitment to successful project handoff
38. 38U.S. Department of Transportation
38
EAR Program Status
Nine solicitations
□ 85 projects; 21 active
□ $87M federal, $28M match
200+ Initial stage investigations
□ 35 resulted in research investments
□ 9 summary reports; no investment
39. 39U.S. Department of Transportation
Recent Awards
Mobile data
□ University of Maryland
Behavioral economics
□ Penn
□ TTI
Connected simulation
□ University of Iowa
□ Iowa State University
40. 40U.S. Department of Transportation
NRC Associates
Current Research
□ Robotic Air-Coupled Acoustic Array for Highway Structures
□ Cost-Benefit Analysis of Connected and Automated Vehicle
Operations
□ Naturalistic Driving Data Analyses
More Information Located at
□ www.fhwa.dot.gov/advancedresearch/nrc_announcement.cfm
41. 41U.S. Department of Transportation
EAR Program Payoff
Connecting with new partners
Growing scientific capacity and pushing disciplinary frontiers
□ Building tools that accelerate discovery, allow for new
measurements, concepts
Pointing towards new technology, applications