There are many major trends in the technical field. The most interesting one is the development of autonomous vehicle. In addition to cars, buses and trucks, autonomous driving technology is also used for delivery robots in warehouses, industrial parks and large commercial facilities, as well as "last mile" autonomous vehicle and unmanned aerial vehicles used to transport meals, medicines and small packages.
Although it is many years before the full application and production of fully autonomous vehicle (Level 5), with the continuous progress of sensors, computing and connectivity infrastructure and policies, the adoption rate of autonomous vehicle is increasing.
In fact, there are two main classification systems for the level of autonomous vehicle: the National Highway Safety Administration (NHTSA) classifies the continuity of autonomous driving into five levels, and the Society of Automotive Engineers (SAE) classifies it into six levels.
The proportion of SAE and NHTSA is quite similar. For example, Tesla Model S's Autopilot is currently the most well-known car on sale with a certain degree of autonomy, and happens to be in the same level on both levels.
The success of autonomous vehicle is based on solving the need for rapid response time, accuracy and long-term calibration over time, temperature and use.
Perhaps the biggest impact on the adoption rate of autonomous vehicle is that the cost of auto drive system and debugging costs are still high. In addition, certain technologies such as LIDAR are still difficult to use and aesthetically unappealing to consumers. Consumers will definitely resist the clumsy appearance of LIDAR devices on the roof, windows, and rearview mirrors. In addition, continuous maintenance and repair will be required as environmental challenges such as snow, smoke, and dust will inevitably have corrosive effects on external LiDAR modules.
Despite these issues, there has been considerable investment in technologies such as LIDAR in recent years. However, Tesla's Elon Musk and others insist that LIDAR is not necessary, and instead a visual system that combines inertial measurement units (IMUs) and GPS applications is needed.
Sensor Technology in Autonomous Driving Position Sensing
Agricultural equipment - tractors and combine harvesters - was one of the earliest commercial uses of vehicle autonomous driving. In the past decades, the market acceptance and technical progress of ground autonomous vehicle have been positive.
Manufacturers of smart agriculture, heavy construction equipment, and last mile vehicles worldwide demand higher accuracy from their embedded GNSS and INS sensor systems, which must be as precise as possible to ensure highly accurate positioning and accuracy, as well as the safety of operators and nearby workers.
In addition to sensors used to measure position relative to signals from GNSS and GPS satellite networks, there is also a lesser known but equally crucial sensing technology - inertial measurement unit (IMU) sensors.
In most positioning systems, there is an IMU that helps the positioning engine calculate position using physical motion as part of the positioning calculation. This is crucial for highly accurate systems that can calculate system forces, angular velocities, and directions that vary over time and temperature. IMU is used in many GPS, GNSS, and INS systems and provides absolute heading, positioning, and dead reckoning. The backbone of any good IMU is the system performance measured by the Allan bias of the sensor (especially the bias stability and angle random walk of the gyroscope).
IMU is used in many high-precision applications. Currently, high-precision and expensive IMUs are used in many high-precision applications, from missiles, commercial aircraft to drone control and navigation applications. In automotive applications, the selection options for high-performance IMUs have increased threefold, and the cost has consistently prevented car manufacturers from using higher performance IMUs for autonomous driving applications. With the increasing demand for autonomous performance, the demand for functional safety devices also increases, while the pursuit of low cost is almost linearly growing.
With the increasing demand for autonomous performance, the demand for functional safety devices also increases, while the pursuit of low cost is almost linearly growing.
Overall, autonomy has made significant progress in vehicles, drones, and last mile delivery robots, which will help reduce our carbon footprint, improve efficiency and productivity, and potentially save lives. However, there are many challenges that need to be addressed. However, with the technology in the current market and the constantly developing sensor technology, autonomous vehicle will be able to drive safely on our highways and urban centers in about ten years.
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