DOE · DOE-353 · record R3295
AI used for predictive modeling and real time control of traffic systems
Department of Energy · PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Overview
- Development stage
- DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Does not meet any requiremnts for high Impact use case
- Start date
- 2024-10-01 (day precision)Source: 2024-10-01T00:00:00
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Transportation
- Operational functions
- Forecasting and prediction Derived by keyword rules; see methodology
Problem the AI is intended to solve
Produce high-quality, contextually relevant, and coherent responses or content based on user input.
Expected benefits
Reduces traffic congestion, energy use, and greenhouse gas emissions.
System outputs
Produce high-quality, contextually relevant, and coherent responses or content based on user input.
Technology
- AI classification
- Reinforcement learningSource: Reinforcement Learning: AI trained through trial and error using rewards and penalties to optimize decision-making policies.
- System name(s)
- R&D User
- Custom-developed code
- No
- Public source code
- Not reported
Sourcing
- How it was built
- Contract and in-houseSource: c) Developed with both contracting and in-house resources
- Vendor (as reported)
- Microsoft
- Vendors (standardized)
- Microsoft
A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.
Data and privacy
- Involves PII
- No
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- Yes
- Demographic features
- k) None of the above
- Training and evaluation data
- No
- Federal Data Catalog
- No
Governance
0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Pre-deployment testingNo answer reported
AI impact assessmentNo answer reported
Independent reviewNo answer reported
Ongoing monitoringNo answer reported
Operator trainingNo answer reported
Fail-safeNo answer reported
Appeal processNo answer reported
User and public consultationNo answer reported
Potential impacts and how they were identified
Not reported