Select locations that perform. Validate traffic demand and customer demographics before signing a lease.
Via
C-SiteAADT, turning movements, and mobility metrics — validated for exact intersections, not street averages.
Show clients neighborhood intelligence that closes deals. Commute data, income, and traffic — on an AI map.
Via
Map AIIdentify bottlenecks, model traffic impact, and benchmark road network performance.
Location intelligence reports for retail site selection. Traffic + demographics at any address.
Highly accurate traffic data for civil and transportation engineers.
Road network performance visualization and mobility improvement planning.
ITS development and before/after evaluation for smart traffic systems.
Turning movement counts and delay analysis for intersections and signal timing.
01
Multi-source ingestion
We aggregate vehicle detection sensors, GPS traces, camera networks, and demographic datasets — continuously, 24/7, across all US roads.
02
Proprietary algorithm
Ticon's algorithm cross-verifies all inputs through multivariate analysis, eliminating probe bias and computing true traffic volumes — not sample estimates.
03
Decision-ready output
Delivered as interactive platforms (TrafficZoom, Map AI) or detailed reports (C-Site, Traffic Intelligence Report) — formatted for your exact industry workflow.
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July 8, 2026
Bottlenecks Are Not Always Where Traffic Looks Heaviest
A traffic-analysis blog explaining why congestion bottlenecks often differ from highest-volume locations, and how detailed intraday data helps engineers choose between signal timing, access management, and capital improvements.
July 8, 2026
Historical Traffic Data Turns Development Pressure into Mobility Intelligence
Historical traffic data helps planners understand how new developments change volumes, turning movements, and peak patterns. Ticon’s methods combine continuous coverage, multiple data sources, and validation to support better mobility decisions.
June 29, 2026
Bottleneck Identification Should Precede Urban Growth
This blog discusses how high-resolution traffic data and bottleneck identification can guide effective urban transportation planning amidst growing development pressures.
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