Research On Safety And Security Technology Of Rain And Fog Environment

With the rapid development of the economy,the number of car ownership has increased year by year and the traffic network has increasingly improved.However,the problems exposed by the transportation industry have also become more prominent.To be specific,unscientific traffic planning in early periods triggers safety hazards in road design;road traffic safety facilities are not matched;and the level of traffic management is lagging behind because of low intelligence.Traffic safety is influenced by weather factors,among which rain and fog meteorology comes first.The rain and fog environment increases the risk factor of driving and causes many traffic safety hazards.Therefore,it is of great significance to carry out research on safety and security technology for driving in rain and fog conditions.This paper analyzes the causes of typical road traffic accidents in rain and fog conditions,clarifies the main factors,and proposes traffic management strategies in rain and fog environment.In view of frequent rain and fog meteorology in many of China,the author understands monitoring on rain and fog conditions and the development of early warning and detailedly introduces the monitoring technology,monitoring methods as well as instruments and equipment under rain and fog environment.The early warning system is analyzed from several aspects such as influence factors,level and method of early warning as well as release of early warning information.Since high-speed driving in rain and fog conditions will further aggravate the danger,it is reasonable and effective to adopt speed-limit measures,maximizing the safety of the station.At present,the speed control method is mainly based on static speed limit,which is a fixed speed-limit method and cannot be dynamically adjusted according to weather conditions and real-time road traffic conditions.In this paper,the author proposes dynamic speed-limit measures in the rain and fog environment by establishing LSTM model,predicting dynamic speed as well as se.