Seeing the Line Clearly: Measuring Border Wait Times by Lane

by Erik Vargas, Swapnil Samant and Rafael Aldrete

For anyone who regularly crosses the U.S.-Mexico border in El Paso, “wait time” is not a single experience. A trusted traveler using a dedicated lane may be through the port in minutes, while a driver in a standard lane could be waiting an hour or more, especially during peak periods.

Yet many publicly available border wait time (BWT) estimates still treat passenger vehicle traffic as one stream. That lack of detail makes it harder for travelers to make informed choices and for agencies to manage congestion using the infrastructure they already have.

Researchers at the Center for International Intelligent Transportation Research (CIITR), part of the Texas A&M Transportation Institute (TTI), partnered with the City of El Paso International Bridges Department to explore whether passenger vehicle wait times could be measured reliably by lane type. The pilot focused on the Paso del Norte crossing, where travelers can choose between regular lanes (standard and Ready lanes) or enroll in a trusted traveler program such as Secure Electronic Network for Travelers Rapid Inspection (SENTRI) or Global Entry.

In regions like El Paso, each crossing serves multiple lane types, including regular and SENTRI lanes. Reported wait times are often presented as a single average that combines all lane types at a crossing, rather than distinguishing between them. As a result, drivers may make crossing decisions based on information that does not reflect their specific lane eligibility, leading to inefficient lane use and avoidable congestion.

Testing lane-based measurement at Paso del Norte

Most passenger vehicle BWT systems rely on Bluetooth or Wi-Fi technology, which anonymously detect signals from phones or in-vehicle devices and estimate travel time based on when those signals are observed at different locations. These systems are effective for understanding overall queue conditions, but their detection range makes it difficult to determine which specific lane a vehicle is using when lanes run side by side.

Radio frequency identification (RFID) takes a different approach. RFID has been used for years to measure wait times for commercial motor vehicles, which typically carry windshield-mounted tags. By matching the same tag as it passes two fixed RFID readers, researchers can calculate how long it takes a vehicle to travel from one point to another and associate that time with a specific lane.

Until recently, this approach was not practical for passenger vehicles, also referred to as privately owned vehicles (POVs). Changes in vehicle registration practices in Mexico and the widespread use of trusted traveler programs have increased the number of POVs carrying RFID tags, creating an opportunity worth testing.

During the pilot, RFID readers were placed at two key points along the northbound approach at the Paso del Norte crossing. When the same tag was detected at both locations, researchers calculated the crossing time and identified whether the vehicle used a regular lane or the SENTRI lane.

Because of equipment limitations during the pilot phase, including a limited number of RFID readers, wait times were reported at a broader level rather than for each individual passenger vehicle lane. For this study, researchers segmented results between regular lanes and the SENTRI lane. With additional readers, the same technology could support more detailed and lane-specific wait time estimates, including distinctions among general, Ready and SENTRI lanes.

Over roughly six weeks of data collection in summer 2024, the system produced tens of thousands of usable samples. The results showed that RFID penetration rates were sufficient to generate stable, lane-specific estimates, particularly in the SENTRI lane, where nearly half of all vehicles carried a detectable tag.

What clearer wait times make possible

The lane-based patterns that emerged reflected what many travelers already experience, but with a level of clarity not previously available. SENTRI crossings were consistently short and under 10 minutes. Regular lanes varied, with some wait times extending well beyond an hour.

When researchers compared RFID results to existing Bluetooth-based estimates, an important distinction became clear. Bluetooth and Wi-Fi systems tend to report an average that falls between the experience of different lanes. RFID revealed how that single number can help distinguish meaningful differences that matter when drivers are deciding where to queue.

The research team also explored a complementary approach using cameras and artificial intelligence (AI). By applying computer vision techniques to existing video feeds, researchers were able to identify vehicles, determine their lane of travel and estimate speeds without relying on any onboard tag. While camera coverage during this pilot was not sufficient to calculate full end-to-end crossing times, the test highlighted the potential of AI-based methods to increase sampling rates and support future applications, including pedestrian crossings.

Together, the findings point to a hybrid strategy that can evolve over time.

• Bluetooth and Wi-Fi remain valuable for capturing overall queue dynamics.
• RFID adds precision where lane choice matters most.
• AI-based video analytics offer a path toward infrastructure-based measurement that does not depend on vehicle equipment.

Collectively, these tools can support clearer and more timely information that helps distribute demand across available crossings rather than concentrating traffic at a single location.

In regions like El Paso, where travelers may choose between multiple ports of entry, lane-based wait-time information becomes especially valuable. When accurate, lane-specific data are available across crossings, travelers can select routes that better match their needs, reducing unnecessary queuing and helping make more efficient use of existing infrastructure. Without that information, traffic often converges on the same crossing simply because conditions elsewhere are unknown.

This pilot demonstrates that measuring passenger vehicle wait times by lane is both feasible and increasingly practical. As RFID adoption continues to grow and AI tools continue to be developed, the opportunity to provide more accurate border information will only expand.

Rafael Aldrete is an associate agency director overseeing TTI’s Operations Group and director of CIITR, based in El Paso. Swapnil Samant is a research scientist and manager of the El Paso Research and Implementation Program. Erik Vargas is an assistant research scientist with CIITR in TTI’s El Paso office.