Road Surface Condition Detection based on Road Surface Temperature and Solar Radiation
This paper presents a method of road surface condition detection with road temperature and solar radiation by BP neural network. Because road temperature depends on road surface condition (dry, wet, icy) and solar radiation (mapped to season, geographical location, time, air temperature and air humidity), and there is nonlinear causality between mem, road surface condition can be detected indirectly with road temperature and solar radiation. In experiment, BP neural network was trained with 2208 group data and validated by 192 group data, the detection accuracy reached 90％. It is feasible to detect road surface condition with road temperature and solar radiation.
vehicle safety road detection road temperature solar radiation BP neral network
Lu Junhui Wang Jianqiang
Physics and Information Engineering Institute Jianghan University Wuhan, China State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing, China
国际会议
长春
英文
4-7
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）