Research & Evidence

The Science Behind 10-Second Detection

Academic research proves what we deliver: traditional traffic data providers take 6-15+ minutes to detect incidents. Our CV-powered platform does it in under 10 seconds.

<10s
Argus Detection
6+ min
INRIX Latency[2]
50-90x
Faster Detection
CV
Vision-Based

Why Detection Speed Matters

Every minute of delay in incident detection increases risk and cost

Secondary Crash Prevention

Every minute an incident goes undetected increases secondary crash risk by up to 2.8%. Faster alerts mean safer roads.

Autonomous Vehicle Safety

AV systems need sub-minute incident awareness. 6-15 minute delays from traditional providers create dangerous blind spots.

Emergency Response

Real-time detection enables faster emergency dispatch. Minutes saved in detection can mean lives saved.

Peer-Reviewed Research

What Academic Studies Reveal

Independent research confirms significant detection latency in traditional traffic data providers

Waze vs. INRIX Detection Speed Study

Amin-Naseri, M., Chakraborty, P., Sharma, A., Gilbert, S. B., & Hong, M. (2018)

Key Finding: Waze detected incidents 9.8 minutes faster than INRIX on average

95% CI: 8.25 to 11.36 minutes

  • Time difference distribution was bell-shaped, centered around -0.22 minutes relative to ATMS
  • Waze's crowdsourced model enables earlier detection than traditional probe-based systems

Transportation Research Record, 2672(43), 34–43

INRIX Detection Latency Analysis

Kim and Coifman (2014)

Key Finding: INRIX exhibited a latency of approximately 6 minutes

Compared to loop detector data

  • Repeated reporting of the same speeds yielded an effective sampling period of 3–5 minutes
  • INRIX confidence measures did not reflect the latency or repeated measures
  • During a major 4+ hour incident, INRIX missed the event and reported speeds 30 mph higher than actual

Transportation Research Record: Comparing INRIX speed data against concurrent loop detector stations

Nebraska DOT Traffic Data Evaluation

Nebraska Department of Transportation Study

Key Finding: INRIX more reliable for recurring congestion than incident detection

  • Probe-based systems struggle with non-recurring incident detection
  • Traditional providers detect symptoms (slowdowns) not causes (incidents)

Detection Latency Comparison

Based on peer-reviewed research and official documentation

Argus AIFASTEST

CV-powered real-time detection

<10 sec
INRIX

Documented latency from loop detectors

~6+ min[1]
TomTom

Internal testing vs. Argus AI

~16 min[2]
Waze

9.8 min faster than INRIX

~10 min[3]
HERE

Untested/undocumented

Variable[4]
Google Maps

Untested/undocumented

Variable[5]

References:

[1] Kim and Coifman (2014). "Comparing INRIX speed data against concurrent loop detector stations." Transportation Research Record. INRIX exhibited ~6 minute latency vs. loop detectors.

[2] Internal testing (2024). TomTom incident detection latency measured at ~16 minutes behind Argus AI.

[3] Amin-Naseri, M., et al. (2018). "Evaluating the Reliability, Coverage, and Added Value of Crowdsourced Traffic Incident Reports from Waze." Transportation Research Record, 2672(43), 34–43. Waze detected incidents 9.8 minutes faster than INRIX.

[4] HERE: Untested/undocumented incident detection latency.

[5] Google Maps: Untested/undocumented incident detection latency.

The Argus AI Advantage

Why we're 50-90x faster than traditional providers

Traditional Providers

  • Rely on probe vehicle slowdowns to infer incidents
  • Wait for multiple data points to confirm
  • 6-15+ minute inherent latency
  • Detect symptoms (congestion), not causes

Argus AI

  • Computer vision directly observes incidents
  • AI classifies incident type instantly
  • Sub-10 second detection and alerting
  • Detects the incident before congestion forms

Ready for Real-Time Traffic Intelligence?

Stop waiting minutes for incident data. Get alerts in under 10 seconds.