Remember the Tesla on Autopilot that had hit a stationary truck? The reason may be the one to surprise you or come as a shock. Tesla’s autopilot feature is one of the most advanced driver assistance systems on the market today. It’s designed to help drivers by automatically sensing, steering, braking, and changing lanes on highways. However, like any technology, it’s not perfect.
In a viral video that surfaced on Twitter in 2020, shows Tesla Model 3 smashing into a stationary overturned semi-truck on a highway in Taiwan. The truck driver tried warning the Tesla driver to slow down and notice the truck in the middle of the road. However, the Tesla on Autopilot did not even flinch or lower its speed and crashed right into the truck.
This is not the first time something of this sort happened in May 2016, a Tesla Model S on autopilot collided with a stationary truck in Florida, killing the driver. This Tesla autopilot tragedy highlights the potential risks of using any driver assistance system, no matter how good it is.
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A Tesla Model 3 collided with an overturned semi-truck on a highway in Taiwan. The Tesla is said to be set on autopilot by the driver when the incident happened. The Model 3 Tesla car did not sense the stationery overturned truck and rammed into it on the highway.
So, why did this happen? Investigators believe that Tesla’s radar system failed to detect the truck because it was overturned and was stationarily parked in the middle of the road. The autopilot smart system might have confused the semi with stationary sign boards and other random stationary objects on the road.
The autopilot system relies on radar to detect objects in the road ahead, so it’s possible that the stationary semi-truck confused the radar and caused it to miss the truck.
This is a cautionary tale for anyone who uses any kind of driver assistance system, including Tesla’s autopilot. These systems are not perfect and they should never be used without supervision. If you’re using autopilot, or any other driver assistance system, always be aware of your surroundings and be ready to take control of the vehicle if necessary.
Why the Accident Happened?
Tesla uses cameras and front-facing sensors to make sense of any obstacles along the route. It is not likely that the 12 ultrasonic radars could not sense or detect the semi-truck lying in the middle of the road.
There are a few potential reasons why Tesla’s autopilot system might have caused the car to hit an overturned truck on a highway. The autopilot system may not have been able to properly detect the truck due to its position on the road.
Tesla’s autopilot system may have misjudged the distance to the truck, thinking it was further away than it actually was. Moreover, the autopilot system may have failed to brake in time to avoid the collision. These do make sense from a logical point of view of the collision with a semi-truck.
However, many automobile experts hint toward a more crucial aspect of machine learning in this case. The Tesla neural network might have confused the semi-truck with other stationary objects along the highway. But the cameras responsible for cross-referencing every object along the way should have known better. Maybe because these cameras have never seen an overturned semi-truck before and thought it was a regular overhead signboard on the road.
If Tesla had been working and using a system to work like the LiDAR system, the problem could have been solved potentially. The required system should be able to cross-reference such situations to avoid any fatal mishappening.
How Does Tesla Autopilot Work?
When it comes to self-driving cars, Tesla is leading the pack. The company’s Autopilot system is undeniably the most advanced on the market, and it’s constantly improving. But how does Tesla Autopilot work?
Cameras & Ultrasonic Sensors
The key to Tesla Autopilot’s success is its use of sensors and cameras. The system uses eight cameras to create a 360-degree view of the car. These cameras are supplemented by 12 ultrasonic sensors that can detect objects up to 16 feet away.
Tesla Autopilot also uses GPS to keep track of the car’s location. This information is used to create a map of the car’s surroundings. This map is constantly being updated as the car moves.
Tesla Neural Network
The final piece of the puzzle is Tesla’s neural network. This artificial intelligence system is constantly learning and improving. It processes the data from the sensors and cameras to make driving decisions.
This combination of sensors gives Tesla Autopilot a comprehensive view of its surroundings. But how to sum up all the data to convert 2D into a 3D version for the autopilot to understand what to do? That is where machine learning comes into action.
So, the next time you’re in a self-driving car, remember to thank the machine learning algorithms that are keeping you safe! These systems can identify lane markings, other vehicles, traffic signs, and obstacles in the road. This information is then used to navigate the car safely.
Tesla Autopilot is constantly evolving. The system is regularly updated with new features and improvements. Tesla is also working on adding new capabilities, such as the ability to change lanes automatically. As self-driving cars become more common, Tesla Autopilot will continue to lead the way.
How Many Types of Sensors Are There?
As autonomous driving technology continues to develop, so too do the sensors that are used to power it. Here is a look at some of the different types of sensors that are being used by automobile manufacturers for autonomous driving:
Light Detection and Ranging (LiDAR) is a sensor that uses laser light to map out the surrounding area. It is often used in conjunction with other sensors, such as cameras and radar, to provide a more comprehensive view of the environment.
A radar is a sensor that uses radio waves to detect objects in the surroundings. It can be used to detect both stationary and moving objects, making it ideal for use in autonomous vehicles.
Ultrasonic sensors emit sound waves and measure the time it takes for them to bounce back off of objects nearby. This information can be used to detect obstacles in the environment and determine their distance from the sensor.
Cameras are perhaps the most important sensor for autonomous vehicles, as they provide a real-time view of the surroundings. Camera systems often use computer vision algorithms to interpret the images they capture.
Global Positioning System (GPS) sensors are used to determine the precise location of the vehicle. This information is critical for autonomous vehicles, as it allows them to navigate safely and efficiently.
We all know that self-driving cars are the future. But what many people don’t realize is that machine learning plays a crucial role in making this autopilot technology possible.
Machine learning is a type of artificial intelligence that allows computers to learn from data, identify patterns, and make predictions. This is exactly what’s needed for a self-driving car to be able to make split-second decisions on the road.
Each of these sensors plays an important role in the development of autonomous vehicles. As technology continues to evolve, new and improved sensors will likely be developed to further enhance the capabilities of these vehicles.
Why Don’t Tesla Install LiDAR in Its EVs?
Tesla says that LIDAR is not an efficient technology for autonomous driving because it is expensive and the data it provides is not as accurate as other technologies.
Some experts have argued that LiDAR is not necessary for autonomous driving and that Tesla’s decision to not use the technology may be more about cost than anything else. However, some believe that LiDAR is a critical component of self-driving cars and that Tesla’s decision could ultimately prove to be a mistake.
Recently, Tesla Model Y has achieved the highest overall score under the Euro NCAP’s most merciless protocol to date, shattering its past rounds of safety testing. The findings could be seen as a validation of Tesla Vision, as the tests demonstrated that without radar, the Model Y is even safer — perhaps even safer than before sans the LiDAR. Simply put Tesla cars are as safe as any other vehicle running on AI or without.
Euro NCAP Secretary General Michiel van Ratingen officially stated and congratulated Tesla’s stellar performance saying, “Congratulations to Tesla for a truly outstanding, record-breaking Model Y rating. Tesla has shown that nothing but the best is good enough for them, and we hope to see them continue to aspire to that goal in the future.”
Tesla Model Y scored exceptionally well in the adult occupant, child occupant, and pedestrian protection categories. This strong performance is a result of Tesla’s commitment to safety. All of Tesla’s vehicles are designed with safety as a top priority. Tesla Model Y safety features include automatic emergency braking, lane-keeping assist, active park assist-360-degree cameras, and sensors.
Only time will tell which side is correct, but one thing is for sure: Tesla’s decision to eschew LiDAR in favor of other technologies is certainly an interesting one.
Why Other Automobile Makers Are Using LiDAR?
LiDAR makes the whole data interpretation process to be significantly simplified by using the instant data from the autonomous vehicle’s surroundings. The LiDAR sensors don’t have to depend on the neural network of the vehicle to make sense of the 2D data. Waymo and other leading automobile makers are relating to the fact that how effective LiDAR sensors could be for their vision of autonomous drives.
LiDAR, which stands for light detection and ranging, uses lasers to map out the surrounding environment. This information is then used by autonomous vehicles to navigate safely. Mercedes, BMW, Volvo, General Motors, GMC, and other leading automobile makers are already using LiDAR sensors for autonomous models.
Tesla is an automobile company that is not in favor of LiDAR sensors. Elon Musk, Tesla owner and CEO even said that the LiDAR technology is unnecessary and ugly. Well, that to some extent is true as the big size of these LiDAR sensors is not very adorable. But the size or the looks of it do not matter in front of the safety aspect it could bring.
Leading automobile makers across the globe are in favor of using LiDAR for the added benefit of instant data interpretation over-relying on machine learning alone. However, Tesla & Toyota beg to differ and consider their machine learning or neural network to be enough for their autonomous approach.
Elon Musk is not very pleased with LiDAR technology but LiDAR could potentially save some lives in such confusing situations where the sensors do not know what to do. The semi-truck collision is a reminder of how fragile depending on cameras and ultrasonic sensors could be. LiDAR sensors could possibly be successful to detect the semi-truck in this situation. According to Tesla,
“All new Tesla cars have the hardware needed in the future for full self-driving in almost all circumstances. The system is designed to be able to conduct short and long-distance trips with no action required by the person in the driver’s seat.”
It’s important to remember that Tesla’s autopilot system is not perfect, and accidents like this can happen. However, Tesla is constantly working to improve the system and make it safer. Hopefully, future versions of autopilot will be able to avoid accidents like this one.