AI for Smart Corridor Traffic Optimization

Coordinate signals, C-V2X data, and multi-modal flows to cut delays, emissions, and crashes along smart corridors.

Congested corridors need adaptive control. AI ingests detectors, C-V2X, and camera analytics to optimize signals, prioritize transit, and reduce crash risks with real-time coordination.

VRU alerts (peds/cyclists) and speed harmonization.

Work-zone and incident-responsive plans.

Bus bunching mitigation; headway adherence.

live demo · related simulation● LIVE

Real-time detector and C-V2X feeds; QA/QC.

Video/CV analytics for VRU and conflicts.

Transit/freight data and curb sensors.

Frequently asked questions

What reports are available regarding delays, emissions, and safety performance within the simulator?

Reports on delay, emissions, and safety surrogates.

Can you explain the concept of the instrument corridor – specifically concerning detectors, RSU units, and CV systems – and its associated key performance indicators?

Instrument corridor (detectors/RSU/CV) and baseline KPIs.

How do I implement adaptive timing within the advisory mode functionality, and what validation process should be followed to ensure safety and Vulnerable Road User metrics are maintained?

Deploy adaptive timing in advisory mode; validate safety/VRU metrics.

What adjustments can be made to prioritize transit or freight traffic, and how does this impact the tuning of green waves and eco-timing strategies within the simulation?

Enable transit/freight priority; tune green waves and eco-timing.

▶ Try it live

Everything above runs in your browser — open Hash Function Avalanche Visualizer and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Hash Function Avalanche Visualizer simulation