LiDAR, which stands for Light Detection and Ranging, is a popular remote sensing method used for measuring the exact distance of an object on the Earth surface.

This remote sensing method uses light in the form of a pulsed laser to measure ranges to the Earth, these light pulses combined with other data recorded by the airborne system generate detailed information about Earth and its surface elements. The main components of the LiDAR system are a scanner, laser and GPS receiver. Other components are photodetectors and optics.

LiDAR sensors send out infrared light and measure the time it takes for the light to bounce off an object and back to the sensor, creating a three-dimensional map. However, there are two different types of LiDAR: Time of Flight (ToF) LiDAR and frequency-modulated continuous-wave (FMCW) LiDAR.

The ToF type is the most common form of LiDAR on vehicles that map their surroundings by measuring pulses of light that it sends out and bounce back. The other form of LiDAR, FMCW, sends out a continuous stream of light to map its surroundings. This form of LiDAR has a limited field of view, so vehicles with multiple LiDAR sensors are typically using these, while ToF typically has a 360-degree range, allowing for a single device to do the job.

LiDAR system can be used for natural and man-made environments. Scientists use LiDAR to create accurate maps, create digital elevation models and for various other applications. Government and private organisations use drones, helicopters for acquiring LiDAR data. LiDAR technology is also able of detecting more nuanced objects such as the painted lines dividing lanes of traffic and road features.

These days most vehicles use a variety of cameras, sensors and radar to enable features like parking assistance, blind-spot monitoring, adaptive cruise control. Recently,  ARGO AI suggested that recent developments in their LiDAR technology allows them to detect items up to 400 metres away, and even improve their capabilities in low light conditions.

In self-driving vehicles, the LiDAR map is vital, as it helps to see their surroundings. General Motors uses LiDAR maps with its super cruise. They combine map data with onboard sensors. As a result, the LiDAR map provides specific details about turns, exits. This vehicle itself is not outfitted with LiDAR, as a result, it uses LiDAR created map from supplier Usher that is updated quarterly.

For Roads, which can change in different seasons like in Canada, relying on LiDAR maps can be problematic, in such cases, onboard LiDAR sensors are preferred.

Using LiDAR can complete self-driving cars as when Radar struggle in detecting the exact position, shape, size of the object, all these elements are important for self-driving cars, but radar works well in fog where LiDAR struggles. Similarly, cameras can recognise objects well, but they struggle in low light whereas LiDAR works well in low light conditions.

The reason for LiDAR to struggle in the snow is when a laser emitted by LiDAR hits the snow and raindrops it makes the vehicle think that these are actual objects in the car path. For this Ford devised a solution according to which when a laser hits a snowflake or raindrop a part of it will hit snowflake and rain and another part will be diverted towards the ground, so when the algorithm will create a picture by listening to echoes from diverted lasers, it will create a picture of the ground plane as a result. By recording everything in the way of laser you can create a whole ground plane and then can be distinguished when a snowflake is a snowflake.

Autonomous driving technology has the potential to be one of the most vital time-saving technologies and the way LiDAR research and development is going it seems we can see LiDAR creating more efficient autonomous vehicles in future.

written by Jasmeen Gill 


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