San Jose's AI street pilots show measurable gains for buses and basic services
San Jose, California, is pairing computer vision and smart traffic signals to attack the basics: smoother bus rides and faster fixes for street hazards. The city's second-phase object detection pilot flagged nearly 70% of issues before residents reported them, and surfaced 50% more non-pothole hazards like debris, mattresses and overgrowth.
"It does transfer the responsibility of reporting from the residents to the city itself," said Stephen Caines, San Jose's chief innovation officer. "Once we fully integrate this into the system, I think it would be great to see over time if we actually see a reduction in manual 311 reports."
What the street hazard pilot delivered
Mounted cameras and computer vision identified potholes, dumping and debris during routine city vehicle routes. That early detection let crews act before problems escalated. "It really enables us to identify issues before they become worse," Caines said.
The practical upside for operations: fewer missed issues, faster cycle times and a path away from reactive 311 intake. Over months, this kind of detection can compress maintenance backlogs and cut repeat visits.
Transit signal prioritization is speeding buses
San Jose also rolled out AI-powered transit signal prioritization citywide. By reading real-time traffic and granting buses more green lights, average bus speeds are up 20%.
On two routes tested in 2023, the system cut red-light wait times by 50% and kept buses on schedule. Those results cleared the way for deployment across all routes. "Being able to advance transportation gains is something that touches almost every San Jose resident," Caines said.
The city has used a similar approach for first responders since 2018. Emergency vehicle preemption strings together green lights using GPS and cellular data so fire, EMS and police can reach scenes faster. Officials also hope to extend prioritization to school buses countywide.
Funding and partnerships that made it possible
The street hazard pilot is supported by a grant from the Toyota Mobility Foundation. The traffic signal effort was delivered with traffic software provider LYT and the Valley Transportation Authority.
According to Caines, the city combined five grants to pay for the work, with roughly 90% of funding from state and federal sources. The projects were modular, affordable and quick to deploy-useful framing for any city running lean budgets.
Why this matters for city operations
"If you want to know how well a city's government is working, look at the basics - how buses run, how parks are taken care of, how fast potholes are filled," said Mayor Matt Mahan. San Jose's pilots target those core metrics.
- Fewer resident reports are needed as city vehicles "self-report" issues.
- Maintenance becomes proactive instead of complaint-driven.
- Transit reliability improves without adding buses or drivers.
- Clear KPIs: time-to-fill potholes, 311 volume, bus on-time performance, red-light delay.
How other cities can start
- Leverage existing fleets: equip garbage trucks, street sweepers or parking enforcement vehicles with low-cost cameras to scan corridors you already drive daily.
- Start with a narrow scope: one service area (potholes or dumping) and one corridor for signal priority. Set baseline metrics first.
- Handle privacy up front: avoid storing faces/plates, set retention limits, and document access controls.
- Align workflows: route detections straight into work order systems; define SLAs so crews know what to fix and by when.
- Blend funding: stack state/federal grants and small city funds; require vendors to support pilots that can scale if goals are met.
- Train the team: give operations, dispatch and field staff simple playbooks and refreshers as models improve. For structured upskilling by role, see AI courses by job.
Broader AI strategy
These projects fit into San Jose's wider push to use AI for service delivery and internal operations. The city launched an AI training program for staff and sped up housing permitting with automation in the last year.
One theme runs through the work: ship small, measure, expand. With clear metrics and grant-backed partnerships, cities can improve daily services without overspending or overhauling everything at once.
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