Project Summary
Stop-and-go waves on I-680/SR-24 waste fuel, heighten crash risk, and disproportionately burden disadvantaged travelers. Building on small-scale field testing that cut stoppage time by ~70% and hard-braking by 85%, Contra Costa Transportation Authority now seeks to deliver smartphone speed advisories to over 1,000 commuters. This UC Berkeley project supplies the data integrity, governance, and community engagement required for the success of that Phase IV launch. With seven integrated tasks, this project: (1) mines 90 days of PeMS records to flag faulty loop detectors, (2) verifies and repairs cabinets in the field, (3) calibrates remaining detectors with roof-mounted LiDAR ground truth, (4) time-aligns and lane-disaggregates INRIX probe speeds, (5) publishes an IRB-approved Concept of Operations with live detector-health monitoring, (6) recruits over 30% of volunteers from CalEnviroScreen top-quartile tracts through Community-Based Organizations and equip buses, and (7) releases an open-source toolkit and Policy & Scaling Brief. Outcomes include California’s first dual-sensor freeway benchmark, a reusable equity-centered consent framework, and cost metrics that position LiDAR-assisted calibration as statewide best practice, thus compressing start-up timelines and de-risking large-scale connected-vehicle flow-smoothing deployments.
