Image sensor platform will accelerate the deployment of automotive safety features
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As people’s interest in autonomous vehicles continues to increase, the road to autonomous driving is clearly paved with road signs, such as the increase in the deployment of advanced driver assistance systems (ADAS). Image sensors are the basis of these camera-based systems, like the eyes of a vehicle. With the advent of rear-view cameras and 360-degree surround view systems, they allow drivers to see behind and around the vehicle, making driving safer. In addition, the front-view camera system is used to sense what is in front of the vehicle and provide automatic functions that help prevent collisions. . Regulations issued by government agencies and safety ratings such as the New Car Assessment Program (NCAP) are driving the rapid adoption of automotive cameras, prompting automakers to introduce these systems on their automotive platforms, from luxury cars to mass market models. Therefore, according to the data of Japanese market research company Techno Systems Research, the number of car cameras produced globally has more than doubled from 2013 (47 million units) to 2017 (110 million units), and will exceed 200 million units in 2024. .
In addition, the 360-degree surround view system is based on installing four cameras on both sides of the vehicle to provide drivers with low-speed parking and maneuvering advantages. The cameras can also be used to provide lane departure warning and blind spot detection functions to remind the driver before the need to change lanes. The camera is even used to replace the car mirror, in the form of a camera monitoring system (CMS), which allows the driver to see the traditional side-view mirror field of view on the display in the car, without blind spots, and without the need for an external car mirror ( Because jurisdictions can relax vehicle mirror requirements and regulations)-This has great advantages for fuel economy and industrial design. At the same time, the front-view camera system is not only used to display video to the driver, but also to detect what is happening in front of the vehicle to provide additional safety and convenience features. These systems can avoid collisions through automatic emergency braking. When a sudden obstacle in the vehicle path is detected, the car can be stopped and the driver can be assisted by adaptive cruise control. This is especially true under road conditions. It is very useful in heavy traffic.
Sensor considerations
Although all these applications use image sensors as the core components of the camera, they usually have different requirements for some parameters, such as image quality, resolution, and sensor size. For example, the image quality required by a camera used to display images to the driver (such as a rear-view camera) may be different from the image quality required by a front-view camera for perception, which incorporates algorithms to provide automatic emergency braking ADAS functions . Similarly, the resolution required by the image sensor to achieve a specific display format will be different from the resolution required for computer vision applications. The latter requires an accurate minimum number of pixels for an object to be used in the algorithm to correctly detect and recognize it. Converted to the requirement of sensor resolution.
In the front-view camera system, computer vision algorithms use image sensor output to detect pedestrians, vehicles, and objects and make decisions. It requires training on a series of images obtained through thousands of hours of test driving, which is a very costly approach. . These images need to be collected using the same system as the one introduced in production, and the image quality needs to be set before collecting this data set. The adjustment and development of this image quality requires engineers to work in conjunction with the sensor and control it through appropriate automatic exposure and automatic white balance technology to automatically output the best image as the scene conditions change. Computer vision algorithms that are then trained using these captured images cannot subsequently be run on cameras composed of image sensors with different characteristics or tuning, because they have been adapted to recognize the profile of a given data set. Scalable image sensor platforms provide the same performance and similar characteristics, with different resolutions, greatly reducing the workload and cost required for manufacturers to work on multiple platforms, because they can actually reuse engineering development work and The training data set of the image.
Imaging challenge
When considering any automotive imaging system, the performance of the image sensor and the ability to capture a wide range of scene content or dynamic range is a key parameter. The dynamic range measures the contrast of the scene captured by the sensor, or simply put, it can handle very bright areas and dark areas or shadows in the same scene well. This is a common problem with car cameras. When you consider that in the evening when the sun goes below the horizon, the car will drive under an underpass. If the dynamic range of the sensor is too low, key details in the scene may be ignored, causing the driver or the computer vision algorithm to not notice the objects in the scene, resulting in an unsafe situation.
Another aspect that manufacturers must deal with now is the increasing use of light-emitting diodes (LEDs) in traffic signs and automotive headlights and taillights, which adds to the challenges of automotive imaging. LED lighting is usually controlled by pulse width modulation (PWM): LEDs are switched with different duty cycles to control the intensity of light and save power. The speed is too fast for human eyes to perceive. However, although our eyes cannot perceive the flickering of these lights, the image sensor usually captures when the LED is switched on and off. This means that the image sensor output will show this flickering effect when displayed as a video. This is what we don't want and may cause safety issues-and make things more complicated, there is no standard for the frequency of using pulsed LEDs in vehicles or traffic signs. For front-view cameras with computer vision algorithms, the flicker effect means that traffic signs may be misunderstood or missed completely, while for vision applications such as CMS or rear-view cameras, it can make drivers distracted and confused.
Put this scene in the background and imagine a scene with a high-brightness source, such as the sun under the horizon, and some darker-looking details, such as a pedestrian on the side of the road in the shade of a nearby tree. To capture this high dynamic range scene, common image sensors will compensate for the bright parts of the scene by using a shorter exposure time to avoid saturation and overflow of the scene. In the case of pulsed light sources (such as car LED headlights) in the same scene, the short exposure time used to capture the bright details of the scene will cause the image sensor to capture a frame when the headlights are actually turned off. Although it will then merge multiple exposures to output high dynamic range images, in bright daylight scenes, some or all of the exposures described above will ignore the LED and cause the headlights to flicker. If you extend the exposure time and try to capture the scene when the LED is turned on, the part of the scene illuminated by the strong light will be overexposed, greatly reducing the dynamic range, losing details, and ultimately resulting in unacceptable image quality.
High dynamic range and reduced LED flicker
The solution to this problem is an image sensor that can achieve a larger dynamic range in a single frame, so that it can capture bright areas with a sufficiently long exposure time, and capture pulsed light sources during the "on" period without excessive Expose the scene. ON Semiconductor’s Hayabusa® automotive image sensor platform successfully solves this problem with an innovative pixel technology that enables Super-Exposure. This technology uses an innovative design and process that can store more charge in the sensor, making the exposure time five times longer than conventional image sensors of the same size currently used in cars before reaching saturation. Through this pixel technology, Hayabusa? Image sensor achieves a high dynamic range imaging of more than 120 dB, while reducing LED flicker. 
In order to achieve the effect of suppressing LED flicker while maintaining high dynamic range output, super exposure can be limited to a time long enough to capture the entire cycle of the lowest frequency pulsed LED expected in the scene: if we consider 90 Hz, it is equivalent Exposure time of about 11 milliseconds (during this period, the LED may only be turned on for 1/10 or less of this time). The sensor has a capacity of 100,000 electronic charges and can be exposed for such a long time without losing the details of the bright area, while capturing the pulse signal of the LED "on". Secondly, the shorter exposure time combined with a proprietary on-chip algorithm ensures that the dynamic range is expanded, while retaining the areas in the scene containing the pulsed LED captured by the super exposure, and preventing them from being lost through double exposure. Therefore, the sensor can capture a dynamic range of more than 120 decibels in the scene, while retaining the area composed of pulsed LEDs, which appear to be flickering when a normal sensor is used. This realistic performance makes the Hayabusa platform the best solution for developing automotive cameras that require high dynamic range and reduce LED flicker, and because all products in the platform have the same performance, manufacturers can switch between devices at will, And can reuse most of the engineering work and the data used to train the algorithm from one of the sensors.
Summarize
The Hayabusa platform’s vehicle-compliant image sensors cover resolutions from 1 million pixels to 5 million pixels, are scalable, and provide manufacturers with configuration options for a variety of different applications. The first device of the platform, AR0233AT, is a 2.6 megapixel sensor with high dynamic range and the ability to suppress LED flicker, and it generates 1080p video at a rate of 60 frames per second.
An image sensor platform successfully solved the two major technical challenges in the automotive imaging field, and also solved the actual problems of manufacturers. By creating a platform that provides consistent performance and performance with a series of devices, developers can make full use of thousands of hours of scene data for algorithm training to deploy similar ADAS functions on different vehicles and use the most suitable image for the application sensor. This allows them to deploy high-end, high-resolution systems and cost-effective low-resolution systems to different vehicle platforms with minimal workload. The function of Hayabusa's image sensor platform will significantly help manufacturers advance their ADAS products, thereby bringing more choices to consumers, but more importantly, equipping more drivers with systems that will improve road safety for drivers and pedestrians .