Historical Traffic Data Turns Development Pressure into Mobility Intelligence

Recent retail and infrastructure news points to the same operational challenge from different angles. Firestone, Colorado, is preparing for a 128,000-square-foot Target at Firestone City Centre, a 140-acre mixed-use development. Near Boston, Brookfield Properties and New England Development are planning a large redevelopment of the former South Weymouth Naval Air Station, including 6,500 housing units and 2 million square feet of retail and commercial space. At the same time, new discussions around green bank financing for resilience projects show how municipalities are searching for better ways to fund transportation and infrastructure improvements.

For traffic engineers, planners, and location analysts, the central question is not simply whether these projects will generate more traffic. They will. The harder question is where, when, in which direction, by which vehicle types, and under what seasonal or operational conditions those flows will emerge. That is where historical traffic data, properly collected and monitored, becomes the foundation for mobility improvement.

Ticon’s Traffic Analysis Approach

Ticon’s work starts from a practical premise: traffic is not a static number attached to a road segment. Annual Average Daily Traffic (AADT) is useful, but it is only one layer of a larger transportation picture. A corridor serving a new mixed-use development may show similar daily volume before and after opening, while still experiencing new turning pressure at intersections, sharper peak-period delay, changed weekend patterns, or different truck and passenger vehicle composition. Without historical monitoring, those changes can remain hidden until congestion becomes visible to the public.

In AADT Estimation by Various Methods: Accuracy and Reliability, Gregory Brodski and Alex Chaihorsky describe Ticon’s approach as a “Traffic Information Consolidator” rather than a simple big data provider. The distinction matters. Ticon combines traffic engineering methodology, multivariate analysis, GPS and connected vehicle inputs, traffic detector information, GIS, demographics, traffic organization, and event-related context. The result is not only AADT, but traffic flow volumes at hourly resolution and, in some cases, 15-minute bins, with spatial resolution up to an exact address.

That level of detail is important because short-duration traffic counts can misrepresent the conditions engineers are trying to manage. Ticon’s materials compare conventional collection windows with continuous temporal coverage: a 48-hour count observes about 0.5 percent of the year, a one-week count about 1.9 percent, and some manual approaches using five minutes per hour during peak periods only about 1.35 percent. Those snapshots can miss school calendars, seasonal retail peaks, weather-related disruption, construction detours, weekend shopping behavior, and recurring freight patterns.

Ticon’s methodology addresses this gap through broad and continuous coverage. Internal methodology documentation states that Ticon provides almost 100 percent road network coverage, including more than 97 percent of roads at Functional Road Class 6 and above, while collecting information across permanent and portable counters, GPS data, connected vehicles, GIS, demographics, traffic organization, events, and other sources. Through cross-verification, filtering, and proprietary processing, these inputs are converted into estimates of speeds, volumes, and related traffic performance measures for about 95 percent of roadways. Spatial resolution can reach very short segments, as short as 35 feet, with most analyses operating at small segment lengths suitable for corridor and site-level evaluation.

Practical Applications of Historical Traffic Data

The engineering value of historical data is most visible when conditions change. A new anchor store, housing district, logistics facility, or resilience project does not only add trips. It redistributes trips across approaches, alters peak timing, and changes the reliability of access. In the Firestone example, a 128,000-square-foot Target within a 140-acre mixed-use center will likely affect more than the road directly in front of the parcel. The relevant traffic study area includes feeder roads, signalized intersections, secondary access points, and nearby retail corridors that may experience spillover demand. Historical baselines make it possible to separate normal seasonal variation from true project-induced change.

Ticon’s validation work shows why location-specific estimation matters. In the 2018 AADT accuracy study, Ticon evaluated AADT estimation across Georgia, Nevada, and California using publicly available DOT sources. The study began with 695 counting points, rejected 28 because of detector-based counting errors, and rejected another 30 because of gaps in GPS data. The remaining 637 points were mostly bidirectional, resulting in more than 1,200 estimations. Ticon reported that its AADT estimation accuracy can keep expected error within 20 percent boundaries with 90 percent confidence, while supporting similar accuracy across functional road classes 1 through 6.

For mobility improvement, this is not just a statistical claim. It affects which projects are selected, which signals are retimed, which turn lanes are prioritized, and where access management changes are justified. If a planning team relies on a counter located far from the actual point of interest, especially across several intersections, the resulting volume can be wrong for the decision at hand. Ticon’s report Testing the Accuracy of TrafficZoom™ Against Values Sourced by a Leading Industry Provider found that TrafficZoom™ AADT estimation error was below 14 percent in the evaluated blind test, while discrepancies between another provider’s estimates and TrafficZoom™ exceeded 50 percent even on roads carrying more than 7,000 vehicles per day. The report also warns that site or corridor decisions based on imprecise segment-level traffic values can produce sales or performance projections that differ from achievable outcomes by a factor of two or more.