The Software Technology Institute (STI), a research unit of the government-sponsored Institute for Information Industry, has successfully used artificial intelligence (AI) technology to identify various types of traffic contraventions, which helped reduce traffic incidents in Taichung by 39 percent.
Taiwan has 8.68 million registered cars and 14.65 million registered motorcycles, data from the Ministry of Transportation and Communications showed.
The mixture of cars and motorcycles complicates traffic situations and leads to frequent incidents, STI director-general Henry Meng (蒙以亨) said yesterday.
Photo: Taipei Times
The purpose of developing a transportation safety protection system using AI-based image recognition technology is to make roads safer, Meng said. Not only would it help develop smart driving technology, but would also help identify where traffic incidents frequently occur, he said.
“The key to developing AI technology is data... We used 4 million pieces of data recorded in the Sardina database to train the AI-based image recognition model. We also gradually enhance the model’s accuracy,” he said.
However, the challenge is to be able to use AI-based image recognition technology during rainy and foggy weather, he added.
The system can accurately identify sedans, taxis, motorcycles, motorcycles with riders, freight vehicles, buses, bicycles and pedestrians, he said.
The system was first tested on campus and has since undergone trials in Keelung, New Taipei City, Taichung and Kaohsiung, with recognition accuracy reaching 96 percent, the STI said.
The most common traffic contraventions include unlawful U-turns, running through red lights and unlawful right turns, the STI research team said.
AI technology makes around-the-clock traffic monitoring possible and the deployment of law enforcement personnel more efficient, Meng said, adding that the system helped reduce traffic incidents in Taichung by 39 percent.
“We are planning to introduce an on-device AI evaluation system to evaluate the accuracy of image recognition systems developed by different contractors who are interested in bidding for tech-assisted law enforcement projects around the country,” he said.
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