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Is Lidar Essential to the Safety of AVs?

Is Lidar Essential to AVs?
Is Lidar Essential to AVs?

Self-driving car manufacturers have a few options when it comes to choosing the sensors for ADAS. Radars with different ranges, ultrasound systems, optical cameras and LiDAR are some of the most popular technologies for self-driving cars. Out of these, optical cameras and radars are often used together while LiDAR is used as a standalone system. Is the public going to think that lidar is essential to the safe operation of AVs?

From an article in The Manufacturer by Lestyn Cowan.

Tesla has been firm in its belief that computer vision is the future of self-driving cars. As a result, it is the only player that uses optical cameras as sensors and even dropped radars. The images from multiple cameras are analysed through a neural network which utilises the vast amount of data from all the Teslas to make decisions about acceleration, braking and steering.

On the other hand, LiDAR (Light Detection and Ranging) systems are used by everyone else including Waymo, Uber, Yandex and Toyota. LiDAR uses pulsating lasers to create a 3D map of the surroundings with high accuracy. The movement can be detected using an FMCW radar or by sending two quick pulses to see change in position over milliseconds. A computer uses this data to operate the car on the road.

Tesla’s logic
Tesla has multiple reasons to be at odds with the industry on sensors. The biggest advantage of optical cameras is their extremely low cost. Multiple cameras mounted on a car can provide large amounts of data for the neural network to work on. The process of creating these neural networks is very complex, but Tesla has invested in them and each car improves the current neural networks further.

Elon Musk, CEO of Tesla, has even called LiDAR “a fool’s errand” and “a crutch” over time. The opposition to LiDAR believes humans only use vision to drive and self-driving cars shouldn’t need more than that. They list LiDAR’s shortcomings to back this argument. LiDARs are very expensive compared to optical cameras. They are good at mapping the surroundings but can’t distinguish between different objects. They don’t have the advantage of seeing in colour that optical cameras have.

The case for LiDAR
LiDAR has come a long way over the years. Some shortcomings exist but many have been or are being solved. The cost has become a fraction of earlier costs, and companies are working to bring it down to $250. Recently, movement detection became possible with FMCW radars or through rapid-fire pulses. The system can be integrated with traffic light systems to overcome the colour detection issue when the cars hit the road.

Apart from solving the issues, LiDAR developers make a great case on safety. In 2016, a Tesla Model S was involved in a fatal crash. Since then, the authorities are looking into Tesla crashes with stopped emergency vehicles. LiDAR developers believe their systems wouldn’t miss such objects and could avoid crashes or make them less dangerous. LiDAR’s ability to accurately map surroundings in 3D gives it an advantage over 2D camera images where computer has to rely on limited visual information. At the end of the day, everyone wants a safer car even if the cost is a bit higher.

It remains to be seen whether Tesla’s belief in computer vision is rightly placed or LiDAR proves them wrong. Tesla has the advantage of having cars on the road, but LiDAR is also improving rapidly. LiDAR developers believe their systems are the best way towards Level 5 automated driving. Some believe a system with LiDAR and computer vision might come out as the winner. Even if that is the case, it will be a win for LiDAR developers who spent years improving the system and bringing the costs down.

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