Low-Cost Smart Stop Sign Could Improve Driver Safety

According to the U.S. Department of Transportation, more than half of all roadway fatalities occur on rural roads. Hoping to remedy this, engineers at The University of Texas at San Antonio (UTSA) are building and testing a low-cost, self-powered thermal system that will detect vehicles, improve the visibility of stop signs, and hopefully prevent deaths.

 

Stop signs on rural roads are often difficult to see. According to the Federal Highway Administration, rural roads account for about 70% of the US’ byways and the location for 54% of all fatalities. Without access to a power supply, they are more likely than other roads to lack signals and active traffic signage.

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To improve driver safety, Sara Ahmed and Samer Dessouky, professors in the UTSA College of Engineering, created a low-cost, self-powered intersection detection and warning system. The stop sign uses a multi-pixel passive infrared sensor that detects a vehicle as it approaches an intersection. Once the vehicle is within the sensing range, a signal beacon triggers the stop sign’s flashing system.

  

At this point, the system has a 90% vehicle detection rate and a vehicle classification accuracy of 72%. According to the developers, compared to current traffic sensing technologies in urban areas such as magnetic loop inductors, video image processors and microwave radar, their system consumes less power and offers better accuracy. The new technology is also much less expensive to produce. Current safety systems can cost as much as $5,000. UTSA’s detection promises to be a fraction of the price at $60 to $100 per unit.

 

The low-power rural intersection detection and warning system was developed with support from the Connect program, a collaborative research program that is co-funded by UTSA and Southwest Research Institute. The project team has filed an invention disclosure for the system, which was recently recognized nationally by the American Road and Transportation Builders Association, and expects to adapt the technology to pedestrian detection, for border security and for vehicle-to-infrastructure communication. For more info, visit the University of Texas at San Antonio.

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