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Integrated Modeling for Road Condition Prediction (IMRCP)
NOCoE WebinarAugust 30, 2018
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Agenda and Objectives
• Describe the IMRCP objectives and background
• Review and demonstrate system functions
• Describe stakeholder opportunities• Plans for further research and
demonstration opportunities
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IMRCP Program Objectives
• Develop an integrated system for road condition predictions that…– incorporates real-time and/or archived data and results
from an ensemble of forecast and probabilistic models• atmospheric and road weather and hydrology• traffic• work zones and winter maintenance ops• incidents• special events• demand
– fuses them in order to predict the current and future overall road/travel conditions
– for travelers, transportation operators, and maintenance providers
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Benefits and Applications
Source: Wikimedia Commons
Source: Wikimedia Commons
Source: Wikimedia Commons
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IMRCP Development
IMRCP-1:Tech SurveyConOps, Architecture
IMRCP-2:Model DeploymentKansas City Study Area
IMRCP-3:Model EnhancementOperations Focus
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IMRCP SYSTEM DESCRIPTION
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IMRCP Functions
Operator
MaintenanceProvider
Traveler
EmergencyResponder
Work ZonePersonnel
Wx DataService
Hydro DataService
SocialMedia
Maint DataService
TMC/ATMS
Traffic Data Service
Mobile (CV)Data Service
Road WxData Service
Collect
Dynamic Traffic Assignment
(DTA) Forecast
Alert Route
Archive
Geo Services
Data Services
Export
Web Services
Mobile Application
Store
Util System
Machine Learning Traffic
Prediction
Road Weather Forecast
Hydrologic Forecast
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Phase 2 Study Area Sources
Traffic Signal Detector ASOS Station LinkDMS Ramp Detector StormWatch/AHPS Bridge
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DEMONSTRATION
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IMRCP-2 LESSONS LEARNED
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IMRCP-2 Lessons Learned
• The quality of IMRCP results is dependent on foundational systems– Network models– Traffic data availability
• Expand focus beyond the workday– System has to account for “unusual” events
• Invest in calibration and testing– Phase 2 provided system shakedown– Phase 3 needs to focus on traffic and event
details
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IMRCP-2 Lessons Learned
• Report exceptions rather than the norm– Operators know generally what to expect– System needs to focus on “what’s different” or
“unusual”
• Encourage direct integration of IMRCP outputs into ATMS– Notifications are more useful if directed to the
normal operator interfaces
• Develop scenarios for using traffic prediction– How could predictions change operation
decisions?
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NEXT STEPS
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Phase 3 Objectives
• Enhance IMRCP relevance to transportation system operations– Improve the accuracy of the traffic prediction
results– Make the model area more consistent with the
(KC Scout) operations focus– Make the interfaces more useful
• Operate the system over a sustained period (two full years)
• Investigate model automation and replication
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IMRCP-3 Study Area
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IMRCP-3 Next Steps
• Implement the enhancements– Expanded study area– Enhanced TrEPS traffic model– Bayesian model
• Deploy enhancements prior to 2018-19 winter weather season
• Work with KC Scout and other stakeholders to assure utility for operations support
• Operate and evaluate over two years
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STAKEHOLDER OPPORTUNITIES
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Stakeholders
• A stakeholder Core Working Group is shaping the research and demonstration– Development webinars: monitor and review the
progress– Operational planning: help set the objectives and
expectations– Final project experience review
• The broader Operations community can participate through the webinar and conference updates
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Stakeholder Event ScheduleStakeholder Activity Timeframe OutcomeCWG IMRCP-3 Kick-off Meeting
Early July 2018 Describe accomplishments through Phase 2 and set up Phase 3
NOCoE webinar August 2018 Increase awareness of opportunities and applications
CWG IMRCP Design Consultation Meeting
Late August 2018 Obtain guidance and feedback on system
Road Weather Management Stakeholder Meeting
September 2018 Increase awareness of opportunities and applications
CWG Pre-winter Operational Planning
Nov-Dec 2018 Plan for system use, performance measures, and reporting
CWG IMRCP Operational Experience Review 1
Spring 2019 Review experience and solicit feedback for evaluation
Broad stakeholder webinar Summer 2019 Increase awareness of capabilities and experience
CWG Pre-winter Operational Planning
Nov-Dec 2019 Plan for system use, performance measures, and reporting
CWG IMRCP Operational Experience Review 2
Spring 2020 Review experience and solicit feedback for evaluation
Broad stakeholder webinar Summer 2020 Increase awareness of IMRCP capabilities and experience
Final CWG Meeting Summer 2020 Describe accomplishments, evaluation results, and final deliverables; solicit concepts for further deployment and next steps
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Summary
• Integrated Modeling for Road Condition Prediction can extend operational awareness from the “now” to the “what next”
• The Kansas City deployment has demonstrated the flexibility and extensibility of the models and framework
• Extended and new model deployments will move from demonstrating IMRCP capabilities to assessing decision support applications
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QUESTIONS?
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Contact
• TPM: Gabe Guevara, FHWA– [email protected]
• Development: Kyle Garrett, Synesis Partners– [email protected]
• Lead User: Nancy Powell, KC Scout– [email protected]