Automated Data Pipeline Ingestion
Automatically ingests existing geometry, turning movement counts and timing plans for optimization using your network data. Optimize the individual intersection or across connected corridors.
Optimiseur de signal
Reimagine signal retiming for intelligent networks
Streamline signal retiming by automating the most time-consuming parts of the workflow—from identifying where to act to generating optimized timing plans.
Current signal retiming workflows are slow, manual, and expensive.
Lengthy Retiming Cycles
Retiming typically happens every 3-5 years and can take months to complete, making it impossible to respond to evolving traffic patterns.
Manual Data Friction
Teams manually gather geometry, counts, and timing plan data. This manual entry is time-intensive and error-prone.
Engineering Complexity
Complex desktop tools often require specialized engineering expertise, forcing agencies to outsource critical operations and wait on external timelines.
Cut retiming time by up to 50% with automated analysis
Signal Optimizer uses an AI-based Genetic Algorithm to generate HCM-compliant timing plan recommendations tailored to your city’s objectives in minutes by automatically ingesting geometry, counts, and timing data.
Objective-Based Optimization
ecommends optimized timing plans for splits, cycle lengths, offsets, and phase sequences against your agency’s objectives using the Genetic Algorithm – reducing delay, improving progression, supporting multimodal priority or reducing fuel consumption with audit-ready reports.
Engineer-Ready Outputs
Produces engineering-ready exports (PDF, CSV, UTDF) to support your existing review, validation, and implementation workflows. Validate easily against industry standards (MUTCD) or agency standards with Mateo.