Neural Sentient · Road Safety

See risk before it happens. Rehearse the fix in a twin.

A dynamic road-safety platform for DOTs and transportation authorities. See risk before it happens, simulate the fix before you deploy it, measure the outcome after you do.

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Watch it work

75 seconds, no narration: set the scenario, run the prediction, pick countermeasures, and replay the simulated result on the corridor twin.

See risk. Test a fix. Deploy the one that works.

A single workflow — not three disconnected tools — from prediction to activation.

See risk before it happens

Pick a date, time, and weather condition. Neural Sentient projects the conflict profile across your corridor, intersection by intersection.

  • Condition-aware: weather, time-of-day, events
  • Forward-looking — a forecast, not yesterday's heatmap
Neural Sentient interface showing predicted crash severity as 3D columns along a corridor with recommended countermeasures

Test a countermeasure in a digital twin

Before anything changes on the street, every candidate countermeasure is tested in a microsimulation of your actual corridor.

  • Projected Crash Modification Factor per countermeasure
  • Stack multiple, compare combinations
Neural Sentient simulation running for selected countermeasures with Crash Modification Factors

Deploy only what's proven to work

Measured conflict reduction, near-misses, and critical events — baseline vs. intervention, side by side.

  • If the numbers aren't there, the countermeasure doesn't ship
  • Closed-loop: activation feeds the next decision
Simulation complete — conflict reduction, total conflicts, near misses, and critical events for the tested intervention

Simulated on the M Street Corridor

Scenario results from the pilot corridor's digital twin. Field before-and-after measurement follows as the pilot accrues data.

3.4×
Game-day surge

Simulated vehicle-pedestrian conflict volume multiplied on Nationals game days, exactly the kind of event a static safety plan cannot absorb.

38.2%
Game-day reduction

In simulation, a Leading Pedestrian Interval alone cut vehicle-pedestrian conflicts under game-day conditions.

47.9%
Best combination

Stacking countermeasures produced the strongest conflict reduction across the simulated scenario set.

36.8%
Worst-case floor

Even the hardest simulated scenario, a rainy game night, still cleared a meaningful reduction.

Deployment

Cloud-hosted. Standards-compliant. No rip-and-replace.

How it installs

  • Cloud-hosted core, API-driven deployment
  • Camera-flexible sensing, uses existing traffic cameras or compact GDS edge units
  • Integrates with existing signal controllers
  • Per-intersection isolation, per-corridor rollups

Standards

  • Signal-system integration via your existing management system
  • MUTCD-compliant message-sign content
  • Role-based access for planners, operators, supervisors
  • Audit trail on every activation

Who it's for

  • State and city DOTs
  • Transportation authorities and MPOs
  • Corridor managers and traffic engineering teams
  • Safety and Vision Zero programs
Pilot corridor M Street SE, Washington DC
Intersections 9
Pilot window Summer 2026
Deployment model Cloud, SaaS

Ready for a pilot?

Neural Sentient is ready for corridor pilots with DOTs and transportation authorities. Reach out and we'll scope a deployment for your corridor.

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