Skip to main content

Utah intersection Lidar traffic management from Seoul Robotics

Firm says signals at Salt Lake City installation are first to be Lidar-controlled in US
By Adam Hill July 8, 2024 Read time: 2 mins
Lidar sensors are at each corner of the intersection, and create a digital twin (image: Seoul Robotics)

Seoul Robotics has deployed its Lidar-powered traffic signal system in Utah, US.

Installed at the junction of State Street and 5900 South in Murray, Salt Lake City, this is the first intersection in the US where traffic signals are controlled directly by Lidar technology, Seoul Robotics says.

The Utah Department of Transportation (UDoT) wanted advanced sensor technology that can detect, count and track vehicles and other road users under any weather conditions. 

The installation is powered by Seoul Robotics' 3D Perception engine, housed in a compact edge device, with Lidar sensors at each corner of the intersection, which create a digital twin which feeds data to optimise traffic flow and reduces congestion.

Local distributor Gades Sales Company has ensured the system is integrated into local infrastructure, while Blue Band's software translates the data from the 3D Perception Engine into signal commands compatible with existing traffic controllers. 

Seoul Robotics says the solution "mounts directly onto existing infrastructure without significant road work and infrastructure changes". 

Traffic management features include precise stop-bar detection, advanced vehicle detection up to 300 feet from the stop bar, and red-light running. The system has a vehicle counting accuracy of 99.8% at the stop bar, the firm says.

 "Since its installation, our Lidar-based traffic management system has consistently demonstrated excellent detection and tracking of objects, ensuring reliable performance across all weather conditions," says Lee Han-bin, CEO of Seoul Robotics.

"This technology not only meets but exceeds the demands of modern traffic systems."

As well as vehicle flow, the system is designed to accurately count and monitor vulnerable road users, such as pedestrians and cyclists at crosswalks and kerbsides.

Seoul Robotics says deep learning and 3D computer vision ensure that all perceived objects are accurately tracked and classified in real time, enhancing safety and traffic flow across multiple road user types.

For more information on companies in this article

Related Content

  • Kistler’s smooth ride on Caltrans info highway
    December 16, 2022
    Caltrans needed a solution to boost its outmoded traffic monitoring capability. Kistler’s KiTraffic Statistics met the California agency’s stringent requirements. And then came Covid…
  • Sign language reduces human error says Clearview
    September 26, 2019
    Wrong-way warning systems and advanced queue detection can help to reduce human error. They can also cut road accidents – and therefore road deaths, says Clearview Intelligence Where were nearly 1,800 deaths on the UK’s roads in 2018 – an average of five people dying each day. The largest single cause of serious injury is crashes at junctions (accounting for 33% of incidents), while the largest single cause of death was run-off road crashes (30%) “With vehicles increasingly being designed with saf
  • ISS launches advanced radar based traffic sensor
    February 26, 2014
    Image Sensing Systems (ISS) will use Intertraffic Amsterdam 2014 to unveil the new non-intrusive, radar-based, Autoscope RTMS Sx-300, an advanced sensor for the detection and measurement of traffic on roadways. All-weather accurate and virtually maintenance-free, with long-term worry-free reliability, the company says the Sx-300 gives the best lane detection capabilities, providing the ability to detect up to 12 lanes of traffic simultaneously. Its all-in-one-concept combines a high-resolution radar and a v
  • MDOT uses connected vehicle technology to clear snow and ice
    January 9, 2017
    Connected vehicle technology is helping Michigan Department of Transportation (MDOT) clear snow and ice from roadways faster, using GPS-based automatic vehicle location (AVL) devices on its winter road maintenance equipment. These systems report where each truck is, and they gather data from other sensors to report details like atmospheric conditions, camera images, and speed and salt application rates for each vehicle.