South Korean researchers have developed AI technology they believe can increase the safety of pedestrian at intersections.

The country’s Electronics & Telecommunications Research Institute (Etri) has been conducting a demonstration of a predictive pedestrian safety AI service at four major intersections in Cheonan. This service can predict pedestrian trajectories to prevent traffic accidents.

This technology goes beyond existing safety systems that simply detect pedestrians to recognise pedestrians who are about to cross but are not yet visible to the driver.

The existing pedestrian alert systems distributed to local governments required manual setting of specific detection zones by humans. This resulted in pedestrians passing near the zones to be perceived as hazards, triggering unnecessary alerts, and there was the inconvenience of having to update detection zones whenever new cameras were installed or their orientation changed. Above all, alerts were triggered only after pedestrians had already entered the road, leaving insufficient response times for drivers. And there were also cases where road sections outside the detection zones were incorrectly identified as safe.

The predictive pedestrian safety service developed by Etri pre-emptively recognises and predicts the possibility of traffic accidents.

The system consists of on-site CCTV cameras, variable message signs that provide alerts to drivers, controllers and remote video analysis servers. Based on footage captured by CCTV, the system automatically generates a ground region map within two seconds, identifying crosswalks and the entire roadway as risk areas.

It predicts pedestrian trajectories and can send risk alerts to drivers via variable message signs about three seconds before pedestrians enter the crosswalk. Based on the predicted pedestrian trajectories, it evaluates the risk level and visually displays risk information on the variable message signs.

Since alerts are triggered only for pedestrians who will actually cross, unnecessary alerts can be reduced and drivers can pre-emptively recognise pedestrians in blind spots when making right or left turns. Currently, this service is installed at four locations, including two near Cheonan Station with high foot traffic and is being demonstrated for right-turning vehicles.

In the future, Etri plans to enhance the system with an edge-server hybrid structure linking on-site devices and central servers. On-site, edge devices analyse video to predict pedestrian risks, while the central server handles edge device control and statistical analysis. Additionally, it plans to gradually implement features such as predicting vehicle trajectories to provide pedestrians with alerts of approaching vehicles through directional speakers, and natural language-based traffic analysis Q&A.

This technology can expand beyond traffic safety to industrial safety sectors such as logistics centres, factories and construction sites. It also predicts the trajectories of people and equipment, such as workers, forklifts, robots and transport vehicles, identifies risky spots, proactively displays situations with a high risk of collision, and provides step-by-step risk alerts to provide more response times for managers. It can automatically create work area maps and provide information tailored to the on-site situation, reduce unnecessary false alerts in various work conditions, and accurately select and send only the necessary alerts.

Etri has applied for international patents for this predictive pedestrian safety system in South Korea as well as in the USA, China and Europe.

The visual memory-based predictive visual intelligence technology processes video input to abstract the visual information, storing and managing it in visual memory. Through integrated analysis, it accurately understands past relationships and current situations, enabling future predictions.

While the existing video analysis is limited to simply recognising objects or actions appearing in the video, predictive visual intelligence technology is differentiated in that it can understand long-term context and even predict future situations by simulating human memory mechanisms that accumulate and recall visual information.

“Through this on-site demonstration, we have proven a new traffic safety standard that predicts the pedestrian trajectory and notifies the driver three seconds in advance,” said Jinyoung Moon, principal researcher at Etri. “We have verified a safety system that automatically understands intersection conditions and proactively sends alerts. We will continue to cooperate with local governments to consistently enhance predictive traffic safety standards.”

The research team plans to commercialise this technology by 2027 by transferring the technology to smart transportation companies. They also plan to discuss additional demonstration with local governments outside of Cheonan to expand the technology nationwide.

Etri plans to expand the demonstration sites with local government’s intelligent transportation systems and develop them into a nationwide pedestrian safety system. Furthermore, it plans to expand predictive safety technology to cars, trains and bicycles.

Founded in 1976, Etri (etri.re.kr) is a non-profit government-funded research institute.