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  3. Daimler, TORC, and Aeva Team Up to Use 4D LiDAR for Autonomous Trucks

Daimler, TORC, and Aeva Team Up to Use 4D LiDAR for Autonomous Trucks

Daimler Truck

Daimler Truck, the world’s largest truck maker, and TORC Robotics, a leader in self-driving technology, have announced a partnership with Aeva, a Silicon Valley startup that makes advanced 4D LiDAR sensors for autonomous vehicles. The three companies will work together to integrate Aeva’s 4D LiDAR technology into Daimler Truck’s and TORC Robotics’ series-production autonomous trucks, which are expected to hit the roads in the next few years.

What is 4D LiDAR, and why is it important for autonomous trucks?

LiDAR stands for Light Detection and Ranging, and it is a type of sensor that uses laser beams to measure the distance and shape of objects in the environment. LiDAR is widely used in autonomous vehicles, as it provides a high-resolution, 3D map of the surroundings, which is essential for navigation and obstacle avoidance.

However, conventional LiDAR sensors have some limitations, such as being affected by weather conditions, sunlight, and other LiDAR signals. They also only capture the static information of the scene without considering the moving objects' speed and direction.

This is where 4D LiDAR comes in. 4D LiDAR is a new generation of LiDAR that adds a fourth dimension: velocity. By measuring the velocity of each point in the scene, 4D LiDAR can not only create a 3D map, but also track the motion and predict the future behavior of the objects. This enables a much more accurate and reliable perception of the environment, which is crucial for autonomous vehicles, especially for large and heavy trucks that operate at high speeds and need more time and space to react.

How does Aeva’s 4D LiDAR technology work, and what are its advantages?

Aeva is a Silicon Valley startup founded in 2017 by two former Apple engineers, Mina Rezk and Soroush Salehian. The company has developed a unique 4D LiDAR technology that uses a frequency-modulated continuous wave (FMCW) approach, which differs from the traditional time-of-flight (TOF) method used by most LiDAR sensors.

In the TOF method, the LiDAR sensor emits short pulses of laser light and measures the time it takes for them to bounce back from the objects. The longer the time, the farther the object. However, this method has some drawbacks, such as being sensitive to interference from other light sources and LiDAR signals and requiring much power and processing to generate high-resolution data.

In the FMCW method, the LiDAR sensor emits a continuous beam of laser light that changes its frequency over time and measures the frequency shift of the reflected light. The higher the frequency shift, the faster the object. This method has several advantages over the TOF method, such as:

  • Being immune to interference from sunlight, weather, and other LiDAR signals, as the frequency shift is unique to each LiDAR sensor and can be easily filtered out.
  • Being able to measure the velocity of each point in the scene, as the frequency shift is directly proportional to the speed of the object.
  • Being able to operate at a much lower power and with a simpler hardware design, as the continuous beam of light does not need to be switched on and off rapidly, and the frequency shift can be detected with a single photodetector.

Aeva claims that its 4D LiDAR technology can achieve a range of up to 300 meters, a resolution of up to 2 million points per second, and a velocity accuracy of up to 0.1 meters per second. The company also says that its 4D LiDAR sensor can integrate other functions, such as camera, radar, and inertial measurement unit (IMU), into a single device, reducing the sensor suite's cost and complexity.

How will Daimler Truck and TORC Robotics use Aeva’s 4D LiDAR technology for series-production autonomous trucks?

Daimler Truck and TORC Robotics have collaborated since 2019 to develop and test level 4 autonomous trucks, which can drive themselves without human intervention in predefined areas and conditions. The two companies have already deployed a fleet of Freightliner Cascadia trucks equipped with TORC Robotics’ self-driving software and various sensors, including LiDAR, camera, and radar, on public roads in the US.

The partnership with Aeva will enable Daimler Truck and TORC Robotics to upgrade their sensor suite with Aeva’s 4D LiDAR technology, which will enhance the performance and safety of their autonomous trucks. Aeva’s 4D LiDAR sensor will provide a more comprehensive and dynamic view of the environment, which will help the autonomous trucks to detect and avoid potential hazards, such as pedestrians, cyclists, animals, and other vehicles, even in challenging scenarios, such as low-light, bad weather, and heavy traffic.

The three companies will work together to integrate Aeva’s 4D LiDAR sensor into Daimler Truck’s and TORC Robotics’ series-production autonomous trucks, which are expected to be ready for commercial deployment in the next few years. Series production means that autonomous trucks will be manufactured at scale and with consistent quality rather than being retrofitted or customized. This will ensure that the autonomous trucks meet the high standards and regulations of the trucking industry and that they can be easily serviced and maintained.

Daimler Truck

What are the benefits and challenges of autonomous trucks for the trucking industry and society?

Autonomous trucks have the potential to transform the trucking industry and society in many ways, such as:

  • Improving the efficiency and productivity of the trucking operations by reducing fuel consumption, emissions, and maintenance costs and by increasing the utilization and availability of the trucks.
  • Enhancing the safety and security of the trucking operations by reducing human errors, fatigue, and distractions and by preventing the theft and vandalism of the cargo.
  • Alleviating the shortage and turnover of truck drivers by offering them more flexible and comfortable working conditions and by creating new opportunities for them to supervise and manage autonomous trucks.
  • Reducing the congestion and pollution of the road infrastructure by optimizing the routing and platooning of autonomous trucks and by enabling the use of alternative fuels and electric vehicles.

However, autonomous trucks also face some challenges and barriers, such as:

  • Developing and testing the autonomous technology by ensuring that it is reliable, robust, and scalable and that it can handle the complex and diverse situations and scenarios that the trucks encounter on the road.
  • Regulating and certifying autonomous technology by establishing the legal and ethical frameworks and standards that govern the liability, responsibility, and accountability of autonomous trucks and their operators.
  • Accepting and adopting autonomous technology by addressing the social and psychological concerns and expectations of the truck drivers, customers, regulators, and the public, and by educating and training them on the benefits and risks of autonomous trucks.
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Daimler Truck

Conclusion

Daimler Truck, TORC Robotics, and Aeva have announced a partnership to use Aeva’s 4D LiDAR technology for series-production autonomous trucks. This partnership will enable the three companies to leverage their expertise and experience in truck manufacturing, self-driving software, and sensor technology to create safer and smarter autonomous trucks that can drive themselves without human intervention in predefined areas and conditions. Autonomous trucks can potentially transform the trucking industry and society in many ways, but they also face challenges and barriers that must be overcome. The future of autonomous trucking is exciting and promising, and closer than ever.

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  • 4D LiDAR technology
  • Autonomous vehicles
  • Trucking industry
  • Self-driving technology
  • Level 4 autonomy
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Gerane
By Gerane , 15 January, 2024

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