Light detection and ranging (lidar) is a remote sensing technology that uses laser light to detect and measure objects. Lidar can measure the distance between objects, as well as their shape, size and other physical characteristics, and can be used in conjunction with AI cameras to improve traffic flow.
From an article in Electronics 360 by Ryan Clancy.
There are several advantages to using lidar traffic cameras over traditional traffic sensors. First, they can see around corners and obstacles, making them ideal for monitoring city streets. It amplifies the amount of data offered to the AI, and ultimately increases the effective range of the camera. This allows for more accurate detection and tracking of vehicles. In addition, lidar can be used to measure the speed of vehicles. This information can be used to adjust traffic signals and other traffic control devices.
Second, they can capture high-precision 3D measurements of their surroundings, giving the AI a better understanding of distances and vehicle sizes. This information can also be fed in a digital model, which traffic engineers and analysts can use to simulate scenarios for construction work, detours, capacity projections and more.
The benefits of lidar traffic cameras have already been demonstrated in a number of pilot projects around the world. In one project in Las Vegas, a network of lidar traffic cameras was used to create a real-time map of traffic conditions. This information was then fed into a self-driving car, which was able to navigate the city with little human intervention.
In a future where the majority of passenger cars are driven by computers, the vehicles will need to have immense sensing and computing power. Yet they will also be highly dependent on smart infrastructure, such as AI/lidar cameras, for over-the-horizon route planning and decision making. To make self-driving autos a reality, these types of cameras could be a necessity at busy intersections.
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Editor’s Note – Lidar cannot “see around corners and obstacles.”
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