Recent news that Virginia has approved a six-year, $28.5 billion infrastructure plan, with funding tied to more than 4,300 construction and infrastructure jobs, highlights that mobility improvement starts long before physical construction begins. It starts with understanding historical traffic patterns before, during, and after disruptions.

This issue also applies to commercial corridors. Recent retail property transactions in Escondido, California, and Bradenton, Florida demonstrate the economic value of traffic-supported locations. Key to effective infrastructure planning, traffic monitoring, or site evaluation is using historical traffic records capturing daily, weekly, seasonal, spatial, and external variations instead of relying on a single traffic count.

Why historical traffic data matters for mobility improvement

Historical traffic data functions as an engineering instrument that helps distinguish routine congestion from construction-related diversion, weekday commuting from event traffic, and stable traffic growth from anomalies.

In the Ticon Impact Analysis Case Study, Jennifer Hager evaluated traffic demand changes due to road construction, special events, and the COVID-19 pandemic. One case showed a 51% decrease in total average daily traffic (ADT) on a closed road, with a 20% increase on an adjacent road. Another showed a 70% drop in eastbound traffic on West View Road during a construction project.

These findings highlight the risks of incomplete traffic monitoring. Using a single AADT value may mislead planners into thinking traffic is lost or growing organically when in fact traffic redistributes due to detours. Such distinctions influence signal timing, lane closure planning, access management, business impact assessments, and project evaluations.

Traffic data collection needs coverage in both space and time

Traditional methods like portable counters and short manual counts lack full temporal and spatial coverage. Ticon’s methodology ensures year-round observations with cross-verified multiple data sources analyzing intra-day, intra-week, and monthly variations.

The Ticon platform covers over 97% of roads classified FRC 6 and above and provides 100% time coverage. It integrates permanent and portable detectors, traffic counters, GPS, connected vehicle data, GIS, demographics, traffic changes, and events to estimate speeds, volumes, and traffic performance for 95% of roads.

Spatial resolution can be as fine as 35 feet with averages around 225 feet; temporal resolution can be as short as 5 minutes or 15 seconds in some cases. Such granularity captures sharp traffic changes near intersections, ramps, work zones, or retail accesses that broader averages obscure.

Accuracy is an engineering requirement, not a marketing claim

Understanding uncertainty is key to improving mobility decisions with historical data. Brodski and Chaihorsky’s study evaluating Ticon’s AADT estimates showed a median average percentage error of 4.78% and a relative root mean square error of 11.97%, with errors typically within 20% at 90% confidence across road classes.

This confidence is vital for public agencies, consultants, and planners needing volume estimates with clear uncertainty bounds to avoid misleading conclusions about congestion or project impacts.

From AADT to intraday monitoring

AADT informs road importance and planning context, but mobility improvements often require finer time intervals. Congestion forms and dissipates within hours or minutes. Signal timing needs turn and approach volumes by time of day. Work zone management depends on knowing when demand peaks and troughs occur.