Signalized corridor studies
Up-to-the-minute data to track performance and pinpoint issues.
Most signal operations teams are still managing reactively
Traditional signal monitoring depends on detectors at specific intersections. Coverage is limited to where hardware exists, and expanding across a full network is expensive and slow. Floating Car Data (FCD), GPS probe data from connected vehicles, provides continuous Signal Performance Measures (SPM) for every intersection, not just instrumented ones. Three situations where this matters most.
Full network visibility is difficult without continuous data across every intersection
For most agencies, signal performance monitoring only exists where detectors were installed years ago. The rest is managed on intuition and annual studies. Probe data gives every intersection a continuous performance baseline, so retiming resources go where data confirms the need.
Signal retiming investments are hard to justify without before-and-after proof
Retiming requires engineering time, sign-off, and budget. The hardest part is proving it worked. Probe data provides the before-period baseline automatically, with no field collection required before the study starts. The after-period impact is measurable at the movement level and by time of day.
A slow corridor doesn’t tell you which intersection is causing the problem
Aggregate corridor data hides where the bottleneck is. Probe-based measures break results down to the intersection and movement level, showing exactly which approach, at which time of day, is creating delay
Our solutions
Signal and Corridor Performance Measures
- Traffic volumes (TMC and mid-block counts), speeds, travel times, and Level of Service (LOS) for every intersection and corridor
- Control delay and stopped delay measured from vehicle trajectories, not estimated from loop counts
- Arrival on Green (AOG) percentage and split failure rate to assess signal progression quality
- CSPI scores each corridor on speed, green/red ratio, and stops per mile, one comparable number across your network
Issue Identification and Diagnosis
- Identify which intersection in a corridor is responsible for LOS degradation, including bottlenecks, downstream blockage, and queue spillback
- Diagnose root causes of congestion, such as inefficient signal timings or poor coordination
Before and After Retiming Validation
- Before-period baseline already exists with no field collection required before the retiming starts
- Measure the after-period impact at the movement level, not just the corridor average
- Prove retiming effectiveness to stakeholders with measured delay reduction, not anecdotal improvement
Network-Wide Screening and Prioritisation
- Rank every intersection by control delay, split failure, or LOS so retiming resources go where they have the most impact
- Covers intersections with no existing hardware, scalable from a single corridor to a city-wide program
Self-Serve, Customizable Dashboards
- Live corridor performance maps and scenario comparison tools using historical data
- Configurable alerts for congestion thresholds and performance anomalies
Our Difference
Access to data where big data is unavailable
- Ad hoc event locations
- Intersections
- Highway ramps
- Corridors
- Work zones
Highest Sample Size
Whether sensor or crowdsourced based, our data captures the highest sample size amongst all other comparable data sources.
Cost Effective
Whether you need to buy or rent sensors for a study or need data plan for managing congestion in ad hoc locations, we have an option that gives you the most data and insights for your budget.
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