Image sensors have become an essential component of modern vehicles, enabling advanced driver assistance systems (ADAS) and autonomous driving features that have transformed driving, making it safer, easier, and more comfortable. This article explores the different applications of image sensors in the automotive sector.
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Image Sensor Technologies
The two main image sensor technologies used nowadays in automotive sectors are CCD (charge-coupled device) and CMOS (complementary metal oxide semiconductor), essentially electronic eyes made of semiconductors. While they both employ photodiodes, their production processes and signal reading techniques differ.
Charge Coupled Device (CCD)
A charge-coupled device (CCD) image sensor consists of an array of capacitors, each carrying an electric charge proportional to the pixel's light intensity. Each capacitor in the array is connected to its neighbor through a control circuit, and the last capacitor discharges its charge into a charge amplifier transferring data in bucket-brigade style.
Complementary Metal Oxide Semiconductor (CMOS)
In contrast, each pixel of a complementary metal oxide semiconductor (CMOS) image sensor is equipped with a photodiode and a CMOS transistor switch, enabling the pixel signals to be amplified separately. The ability to access the pixel signals directly and considerably more quickly than a CCD sensor is provided by manipulating the matrix of switches. Another benefit of each pixel having an amplifier is that interpreting the electrical impulses generated from the recorded light results in less noise.
Applications of Imagine Sensors in Automobiles
Advanced Driver Assistance Systems (ADAS)
One of the primary applications of image sensors in the automotive sector is advanced driver assistance systems (ADAS) technology that automates, simplifies, and enhances car systems to help drivers drive more safely and effectively.
Types of ADAS Technology
There are several ADAS technologies, such as alcohol interlock systems, electronic stability control (ESC), blind spot detection, driver behavior monitoring, automatic emergency brake systems, parking assistance systems, pedestrian detection, night vision, tire pressure monitoring system (TMPS), traffic signal recognition system (TSR), forward collision warning systems, lane departure warning systems adaptive cruise control (ACC), etc.
Working of the ADAS System
ADAS systems employ a combination of cameras, radars, and other sensors to deliver real-time information about the environment around the vehicle. Image sensors are a crucial part of ADAS systems because they provide high-resolution pictures that computer vision algorithms interpret and prevent crashes by using these algorithms to identify obstructions, people, and other vehicles on the route.
Front Facing and Rear Cameras
One of the most popular uses of image sensors in ADAS systems is rear- and front-facing cameras. The front-facing cameras are very useful when low visibility conditions, such as fog or heavy rain, impair driving eyesight. Whereas rear-facing cameras, which provide a good view of the area behind the car, are especially helpful for parking and navigating in confined places.
A 360-degree camera system, which employs many cameras to provide a bird's eye view of the area around the car, is also available on certain vehicles.
Other applications of Image sensors in automobiles include internal use for image sensors in the cabin monitoring system, which uses cameras to watch the inside of the car and track passengers' activities to inform the driver about passenger safety.
Image sensors are also used in advanced vehicle lighting systems by detecting oncoming vehicles and adjusting the beam pattern to avoid blinding the other driver.
IR Image Sensor Employed in Nissan ASV-2
In 2004 an experimental thermoelectric infrared imaging sensors blind spot pedestrian warning system was incorporated in the Nissan ASV-2 that employed four infrared imaging sensors. This system helped alert the driver to the presence of a pedestrian in a blind spot by detecting the infrared radiation emitted from the person's body.
Application of Image Sensors Automobile Manufacturing Sector
Another application of image sensors is in the automobile manufacturing sector. High-speed image sensors employed in the vehicle manufacturing sectors allow for thorough defect identification, particularly in very fast-moving production processes. As a result, quality and process control are also progressively being shifted to imaging systems. Moreover, image sensors ensure micrometre-accurate assembly tolerances, brilliant surfaces around the clock, and defect-free circuits on the increasingly prevalent chips and microcontrollers.
Challenges of Using Image Sensors in the Automotive Sector
Although employing image sensors in the automobile industry has numerous advantages, there are also some drawbacks. For instance, image sensors can be expensive, particularly those used in advanced ADAS and autonomous vehicle systems, making them less accessible to budget-conscious consumers.
Data processing and storage can be complex due to the massive volume of data that image sensors output, specifically in autonomous cars that produce enormous volumes of data that must be analyzed in real-time to guarantee a safe and effective operation. Additionally, image sensors can be susceptible to damage from debris or other external factors like weather conditions such as rain, fog, and snow, which can impact reliability and performance.
The performance of ADAS and Autonomous Vehicles (AVs) systems has substantially increased in recent years due to image sensor technology developments, making them more reliable and precise.
Lidar technology is becoming increasingly popular in ADAS and AVs because it provides highly accurate depth information. Similarly, 3D image sensors can capture depth information, which is essential for depth perception in ADAS and AVs, providing accurate depth information which can be implemented in an automobile to detect and classify objects in 3D space.
Overall, the future of image sensors in automotive applications looks promising, and more advanced sensors providing more accurate and reliable data are expected to support the development of safer and more efficient ADAS and AVs.
Reference and Further Reading
Antony, M.M., Whenish, R. (2021). Advanced Driver Assistance Systems (ADAS). In: Kathiresh, M., Neelaveni, R. (eds) Automotive Embedded Systems. EAI/Springer Innovations in Communication and Computing. Springer, Cham. doi.org/10.1007/978-3-030-59897-6_9
Hirota, M., Nakajima, Y., Saito, M., Uchiyama, M. (2004). Low-Cost Infrared Imaging Sensors for Automotive Applications. In: Valldorf, J., Gessner, W. (eds) Advanced Microsystems for Automotive Applications 2004. doi.org/10.1007/978-3-540-76989-7_6
Image processing in the automotive industry. (2019). Automation and Digitisat.
Sukhavasi, S. B., Sukhavasi, S. B., Elleithy, K., Abuzneid, S., & Elleithy, A. (2021). CMOS image sensors in surveillance system applications. Sensors. doi.org/10.3390/s21020488
What is a CMOS image sensor?: The principle of semiconductor. Nanotec Museum. Available at: https://www.tel.com/museum/exhibition/principle/cmos.html.
What is an image sensor?. Association for Advancing Automation. Available at: https://www.automate.org/blogs/what-is-an-image-sensor.