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Mark Patrick from Mouser Electronics explains about use of Sensor Technologies for Autonomous Vehicles

For an autonomous vehicle to navigate itself safely, it needs to fully comprehend its surrounding environment. Without this knowledge, autonomous vehicles will never achieve the road safety objectives that society expects from them.

Mark Patrick from Mouser Electronics explains about use of Sensor Technologies for Autonomous Vehicles

Meeting the aspirations of passengers and countering societal anxieties concerning autonomous vehicles also depend on the systems having 360-degree awareness.

For a vehicle to ‘see,’ it needs two crucial technologies. First are different types of sensors that can electronically sense objects, their position relative to the vehicle and, if they are moving, their speed. Secondly, computer-based machine learning algorithms need to process the sensor inputs to infer key parameters about the object the sensors can see. Is the object another car, a traffic sign, or a pedestrian? For each class of object there will be a set of related parameters that the vehicle’s control systems will need to know. Many of these technologies already operate in a limited capacity as advanced driver assistance systems (ADAS), but to achieve full autonomy, more sophisticated sensors are required.

Core Sensor Technologies
Three sensor technologies stand out as being crucial for an autonomous vehicle to learn the world around it: lidar, radar, and cameras.

Radar is already used in ADAS functions such as emergency braking and adaptive cruise control. It will continue to provide a key sensing function for multiple purposes at different vehicle speeds, such as automatic parking, highway lane changing, and in slow moving traffic. The latest radar modules operate at millimetre wavelengths (mmWave), typically a frequency of 77GHz, and can rapidly detect the range, speed, and angle of multiple objects irrespective of weather conditions. These recent modules are compact, low-cost, and, with radar’s established track-record, offers a reliable sensing technology. However, radar does have limitations, one of which is how fast and how much object data it can provide.

Lidar operates in a similar way to radar but uses pulses of light from a laser source instead of millimetre waves. It can scan in three dimensions millions of times a second to rapidly create a virtual map of the environment surrounding the vehicle. lidar is becoming widely adopted by vehicle manufacturers for use in autonomous systems since it can create a dynamic overhead view that includes the shape and depth of objects such as vehicles, pedestrians, and road signs. Lidar is a complementary sensing technology to radar, each suiting specific applications. Examples of lidar include the Velodyne Alpha Prime, a high-resolution 128-channel sensor with a horizontal 360-degree field of view, a 40-degree vertical field of view, a detection range up to 300m, and a resolution accuracy of +/- 3cm. With a frame rate of up to 20kHz, it can deliver up to 4.6 million object data points per second. Velodyne Lidar continues to develop next-generation sensors, automotive customers include Ford, Honda, Tesla, and Mercedes-Benz.

Between them, lidar and radar produce a lot of detail for the vehicle’s navigation systems to ingest, but they don’t cover all requirements. Some image detection tasks require a more complex interpretation of the image they have observed—road sign recognition, for example. For this and other similar tasks, high-definition cameras are needed. By placing cameras with wide angle lenses on the front, sides, and rear of the vehicle, a 360-degree real-time view of its surroundings can be achieved. This approach will reduce the risk of blind spots, so that by combining the output from lidar and radar sensors, the autonomous systems will have a truly representative view on which to base its navigation decisions.

As we covered in the previous blog, Vehicle Autonomy: What are the key stages?, achieving full autonomy (SAE Level 5) requires the vehicle to be capable of driving itself at all speeds, in all weather conditions, without any human assistance. Achieving that goal places total dependence on multiple sensors providing a real-time view of not only the road ahead, but everything that surrounds the vehicle, from pedestrians to street furniture. In this blog, we have highlighted three of the principal sensor technologies that autonomous vehicles use—but, in time, other sensor technologies will evolve to complement them. Another critical aspect of autonomous vehicle design will be implementing redundant systems and sensors, so that if one sensor fails, it does not stop the whole vehicle operating safely. Clearly, there is a cost associated with providing redundancy, but making certain that the vehicles do not endanger life is paramount.

Stay tuned for the next autonomous driving blog from Mouser Electronics.

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