10/08/2020
NEWS STORY
This century is full of technological breakthroughs such as laptops, smart TVs, and smartphones. Everyone is enjoying the convenience they offer. But the progress doesn't stop there. Due to the unending need for innovation, it's no surprise that engineers and scientists have created autonomous cars.
These cars are capable of sensing their environment and operating without relying on human command. Many believe that the mechanism of autonomous cars operates exactly like it does on robots. While there are similarities, these cars need STO certified servo motors. Safe Torque Off (STO) is a mechanism that prevents the machine from starting unexpectedly. This function of autonomous cars clears the output of the servo drive so it is torque-free. This means that no external force is acting inside the machine that could lead to unwarranted movements.
However, these aren't the only features of self-driven cars. Read on to learn more!
Vehicle control system
Like robotics, automation of cars relies on sensors and machine learning systems. All the data gathered from these features are translated by powerful processors to execute commands through the actuator.
These cars can create a map of their surroundings based on the positioning of sensors installed on the different parts of the vehicle. Autonomous cars also have radar sensors that monitor the position of cars and obstacles. Their video cameras detect traffic lights and road signals. Likewise, they detect pedestrians to enable the cars to slow down.
If you’re worried about parking, self-driving cars have light detection and ranging sensors, also known as Lidar sensors, that detect pulses of light from the objects around the car. This measures their distance to road edges and lane markings. They also have ultrasonic sensors that detect curbs during parking. Equipped with STO certified servo motors, autonomous cars will not carry out unexpected movements, unless commanded by the user.
computer system organisations
According to experts, there is no standard or "correct" architecture of the components of autonomous cars. However, like any other machine, their computer system organization is categorized into hardware and software. The software includes the process of perception, planning, and control. The hardware, on the other hand, is categorized into the sensors, the V2X technology, and the actuators.
Sensors are components that gather raw information from the environment. This includes the Inertial Measurement Units (IMU), cameras, Lidar, and Radar. Each tool has its advantages and disadvantages.
The radar, for example, gathers bursts of sounds to gauge distance by computing how long it takes for the sound to bounce back to the sensor. While this is an effective measure relative to speeds and distances, it has a narrow field of view and requires multiple units for 360-degree coverage. The Lidar, on the other hand, uses lasers to measure distance. However, these lasers can be obstructed by rain, fog, and snow. Thankfully, these sensors work together to compensate for each other's weaknesses.
V2X technology enables the vehicle to talk and receive information from other agents in the environment. It is subdivided into two components. The vehicle-to-vehicle component (V2V) allows vehicles to communicate with one another. The vehicle-to-infrastructure (V2I), on the other hand, enables the car to communicate with external systems like buildings, lights, and pedestrians.
The last component of self-driving vehicles is the actuator, which is an essential part of the servo motor. These are responsible for moving the system. It is regarded as the "muscles" of the car that respond to the signals from the processors.
embedded and cyber-physical systems
Experts believe that the cybersecurity of autonomous cars is the most crucial among all the machines with Artificial Intelligence (AI). This had sparked the need to upscale the cyber-physical systems of cars.
Image recognition was first recognized as one feature of security in 2016. However, special stickers and graffiti can easily obscure its sensors and undermine its purpose. This led engineers to combine other components to security, like semantic segmentation systems, voice recognition, and Lidar. Unfortunately, these features still pose limitations. This is why machine learning technologies should be tested thoroughly to prevent all AI threats, such as privacy issues, backdoors, poisoning, and adversarial examples.
Domain controllers
Considering the challenges in security and measurement, autonomous cars require a greater number of sensors for a more accurate assessment of their environment. This suggests the need to instal additional electronic control units (ECU) for every component added to the vehicle, such as STO certified servo motors. The ECU controls every subsystem attached to the vehicle. It also ensures that every data collected is transmitted to the servo motor for processing. While it ensures the function of sensors, it also affects the performance of the vehicle. It can likewise add to its complexity and slow down the processing of information.
To address this issue, a domain controller is needed. It's one of the most reliable motor controllers that help replace the function of multiple ECUs by organizing every computer that works on the same network. It decreases the influx of data, making the vehicle process information swift. Besides, a domain controller organizes and secures data from hackers. With this feature, you can detect cyberattacks instantly to prevent further activity.
Conclusion
Automated cars are becoming more prevalent in the automotive industry. However, they still have their limitations. These drawbacks are driving experts to strive to test, retest and modify automotive cars to fit the needs and safety standards of consumers. If you're planning to get a self-driving car, read more articles about them here for more information! It pays off to be an informed buyer to ensure you make the most of your new investment.