A new image sensor for the automotive and autonomous vehicle market

现代汽车拥有令人难以置信的大量技术，提供先进的监控和主动系统，以提高安全性和便利性，包括车道偏离警告，盲点监控，动态巡航控制和自动停车。预计汽车的下一个重大进步将是自动驾驶（即，汽车在人的监督下自行驾驶）和自主（即，汽车自动驾驶，无需人工干预）车辆。虽然现在市场上有数量有限的自动驾驶汽车（例如，某些特斯拉和宝马车型），自主消费汽车还没有。然而，预测表明，到2025年，仅在美国的年销售量就超过500 kcars/年。自动驾驶汽车（AV）需要大量复杂的传感器来管理复杂驾驶任务中涉及的许多功能。常见的是图像传感器（类似于标准相机中使用的那些），以提供用于对象识别、颜色、边缘检测等的信息;然而，这些提供非常少3D数据。3D数据通常使用LIDAR系统获得，LIDAR系统昂贵并且产生需要昂贵的机载处理能力的大数据流。UBC开发了一种新的互补金属氧化物半导体（CMOS）图像传感器（CIS），与当前的图像传感器相比具有重要的优势，并提供3D信息。我们的智能CIS实现了一个集成的片上计算成像传感器解决方案，可以在汽车市场上竞争，有可能在图像和LIDAR传感器市场之间架起桥梁。该提案的目的是对UBC技术在汽车和自动驾驶汽车市场的潜力进行专业和详细的市场评估。

Modern automobiles possess an incredible amount of technology, offering advanced monitoring and activesystems to improve safety and convenience, including lane departure warning, blind spot monitoring, dynamiccruise control and automated parking. The next major advance in automobiles is expected to be self-driving(i.e., car drives itself with human supervision) and autonomous (i.e., cars drives itself with no humanintervention) vehicles. While a limited number of self-driving cars are on the market now (e.g., certain Tesla &BMW models), autonomous consumer cars are not yet. However, forecasts suggest annual sales > 500kcars/year in the United States alone by 2025. Autonomous vehicles (AVs) require a lot of sophisticated sensorsto manage the many functions involved in the complicated task of driving. Common is an image sensor(similar to those used in standard cameras) to provide information for object identification, colour, edgedetection, etc.; however these provide very little 3D data. 3D data is usually obtained using LIDAR systems,which are expensive and produce large data streams requiring costly on-board processing capabilities. UBC hasdeveloped a new complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that providesimportant benefits over current image sensors and provides 3D information. Our smart CIS enables anintegrated, on-chip computational imaging sensor solution that could compete in the automotive market,potentially bridging both the image and LIDAR sensor markets. The objective of this proposal is to conduct aprofessional and detailed market assessment of the potential of using UBC technology in the automotive andautonomous vehicle market.