IEEE Big Data
October 29, 2014

Presentation Outline

• EAR Program Background
   
• Investments in Data Science for Highway Research
   
• Opportunities and Challenges

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

Program Status

• 200+ Initial stage investigations
   
• Seven solicitations resulting in
   
  • 75 projects awarded; 36 ongoing
     
  • $72M federal, $26M match
     
• 8^th closed in 2014
   
  • Topics: Structural assessment, safety data, freight data, freight modeling
     

Focus Areas

Connected highway system concepts

Breakthrough concepts in material science

Human behavior and travel choices

New technology and advanced policies for energy and resource conservation

Technology for assessing performance

Connected Highway Systems

• New Data
   
  • Real time data, data fusion, data analytics
     
• New Communications
   
  • DSRC, Cellular, etc.
     
• Enabling Technologies
   
  • Localization and mapping
     
  • Extended situational awareness
     
  • Adaptive control systems

Human Behavior

• Massive New Data
   
  • Naturalistic driving studies
     
  • Communications metadata
     
  • Social networking
     
• Enabling Technologies
   
  • Automation
     
  • Predictive modeling
     
  • Real time, large scale markets
     

Assessing Performance

• Massive New Data
   
  • Roadside sensors
     
  • Vehicle based sensors
     
  • Structural monitoring
     
• Predictive Modeling
   
  • Actionable information
     

Opportunities

• Use of data to improve
   
  • Highway safety
     
  • Asset conditions
     
  • System reliability, efficiency
     
  • Energy, resource sustainability

• Scientific
   
  • Valid
     
  • Reproducible
     
• Operational
   
  • Actionable
     
  • Efficient
     
  • Accessible
     
  • Secure
     
  • Flexible

Thank You

EAR Program website

David Kuehn
Program Manager
(202) 493-3414
david.kuehn@dot.gov