Design factor optimization of 3D flash lidar sensor based on geometrical model for automated vehicle and advanced driver assistance system applications
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- 作者：C. H. Jang ; C. S. Kim ; K. C. Jo…
- 关键词：Key Words3D flash lidar ; Automotive applications ; Advanced driver assistance system (ADAS) ; Laser scanner ; Ranging sensor
- 刊名：International Journal of Automotive Technology
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：18
- 期：1
- 页码：147-156
- 全文大小：792 KB
- 刊物类别：Engineering
- 刊物主题：Automotive and Aerospace Engineering and Traffic
- 出版者：The Korean Society of Automotive Engineers
- ISSN：1976-3832
- 卷排序：18
文摘
Sensor technologies have been innovated and enhanced rapidly for highly automated vehicle and advanced driver assistance systems (ADAS) in automotive industry; however, in order to adopt sensors into mass production vehicle in near future, various requirements should be satisfied such as cost, durability, and maintainance without any loss of overall performance of the sensors. In this sense, a 3D flash lidar is one of primising range sensors because of no moving parts, compact package, and precise measure for distance by using a laser. In spite of the several advantages, the 3D flash lidar is not commonly used in automotive industry because it is quite expensive for adoption and it is manufactured with only general purpose currently; therefore, the cost reduction and optimal design to satisfy various purposes of ADAS or autonomous driving should be accomplished. In this paper, we propose a novel approach for design factor optimization of the 3D flash lidar based on a geometrical model by using structural similarity between the 3D flash lidar and 2D digital camera. In particular, focal length and area of a receiver (focal plane array and read-out integrated circuit) which directly affect on sensor performance (field of view and maximum detection range) are optimized as the design factors. From the optimization results in simulation, we show that optimal design factors according to various purposes required in ADAS could be easily determined and the sensor performances could be evaluated before manufacturing. It will reduce temporal and economic burdens for design and manufacturing in development process.