A head-on collision between a truck and sedan brought major disruption to the intersection of Mills Road and North Gessner Road early Friday morning. The crash occurred at 4:42 AM on July 31, 2026, drawing a rapid response from authorities.
The impact was severe enough to classify the incident as major. Details on injuries, lane closures, and clearance times were not immediately available from responding officers.
This intersection carries a troubling history. According to LTA data, the Mills Road and North Gessner corridor has logged 23 incidents in the past 30 days—16 of them major. Over the past 90 days, the count climbs to 57 total incidents, with 30 classified as major. The data underscores a persistent pattern at this location: LTA records show 107 total incidents over the past 12 months, 42 of them major.
According to TxDOT CRIS public crash records, the broader corridor (within a quarter-mile) has seen 265 crashes since January 2020, with no fatalities recorded in that span. Contributing factors as recorded by the investigating officer, per TxDOT CRIS, show "Failed To Control Speed" as the leading factor, cited in 66 crashes at the location.
The timing of this morning's crash is notable. LTA data shows most crashes at Mills and Gessner fall outside the typical weekday commute peaks. The single busiest hour for crashes here is 10–11 AM, which accounted for 4 incidents in the 90-day window. This 4:42 AM collision occurred well before that window—a reminder that traffic hazards at this intersection aren't confined to rush hour.
Weather conditions at the time were overcast with temperatures around 78 degrees. While conditions weren't severe, the crash highlights the ongoing pattern of vehicular incidents at this location.
Drivers heading through the Mills and Gessner area should be prepared for potential delays and exercise caution as crews clear the scene.
This report was produced by LTA's editor-designed production system under the executive editorial direction of Dennis R. Mundy, Executive Editor. The system combines our proprietary data pipeline with AI-assisted drafting to deliver verified incident coverage to LTA's editorial standards.