基于道路监控的无人车路径优化控制系统

为充分提高道路的使用率,缓解因视觉盲区及道路拥堵所造成的道路安全等问题,针对无人驾驶技术高速发展的未来对基于道路监控的无人车路径优化系统展开研究。通过模拟道路监控下的无人驾驶,采用高低位相机采集图像,进行图像处理和视觉识别等算法研究,得到车辆和道路的信息选择合适车道并通过车辆进行决策,实现了一种可与道路监控系统相融合的基于高位监控相机与车载低位相机双目融合、多视极线约束的无人车路径优化控制系统。

In order to fully improve the utilization rate of roads and alleviate the road safety problems caused by visual blind areas and road congestion, the unmanned vehicle path optimization system based on road monitoring is studied in view of the rapid development of unmanned technology in the future. By simulating unmanned driving under road monitoring, using high- and low-precision cameras to collect images, the image processing and visual recognition algorithms are studied, and the information of vehicles and roads is obtained to select the appropriate lane and make decisions through vehicles. In this paper, an unmanned vehicle path optimization control system based on binocular fusion of high-level surveillance camera and vehicle-mounted low camera and multi-view polar line constraint is realized, which can be integrated with road monitoring system.