Traffic infrastructure is the support of automatic driving, and the higher the level of automatic driving, the greater the dependence on intelligent transportation.It faces great challenges for automatic driving at present, that manual driving is more than automatic driving on the road.The reliability of the perception system relying solely on the vehicle itself needs to be improved, and the automatic driving decision-making system is not perfect and can not deal with some unexpected situations. Traffic infrastructure is the support of automatic driving, and the higher the level of automatic driving, the greater the dependence on intelligent transportation. In the current intelligent network road system, the traffic infrastructure sensing equipment can obtain the dynamic data of vehicles and environment in continuous space in real time, automatically process the unstructured data, and realize the short-term and micro prediction of vehicle driving combined with the historical data; However, various types of data can not be effectively integrated, and the time delay of information acquisition, processing and transmission is obvious. Based on the analysis of different road levels and different automatic driving levels, this paper discusses the edge node architecture and functions to be realized in the intelligent networked road system, so as to serve the high-level intelligent networked road system.
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