Method and system for analyzing accurate road conditions based on crowdsourcing mode

Abstract

The invention discloses a method and system for analyzing accurate road conditions based on a crowdsourcing mode. The method is characterized by comprising the steps that firstly, terminals transmit GPS position information, pictures and vehicle data information to a server terminal; secondly, on the basis of postback data, the server terminal synthetically judges whether a current vehicle is in the unusual condition or not, and if the vehicle is in the unusual condition, the terminals within the surrounding position range of the current vehicle are called; thirdly, after receiving the calls, terminal devices of the surrounding vehicles transmit GPS track information back to the server terminal and collect the pictures and the vehicle data to be transmitted back to the server terminal; fourthly, the server terminal judges the severity of an accident and the influence range according to the collected data; fifthly, the server terminal converts the accident information into road condition information to be issued to the terminals and informs the vehicles surrounding the happening range of the accident and the processing progress. According to the method and system for analyzing the accurate road conditions based on the crowdsourcing mode, the combined judgment mode of the terminals and the server terminal can be utilized, the complexity of road condition judgment and the high-performance requirement for one-sided determination are optimized, the accuracy and timeliness of the road conditions are improved by the synthetic judgment of the combination of the pictures and the vehicle information, and the method and system have the advantages of being low in cost, high in accuracy, strong in timeliness and expandability, wide in application scenarios and the like, and have great application prospects.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a method and system for analyzing accurate road conditions based on a crowdsourcing model. Background technique [0002] In recent years, with the increase in the number of vehicles, problems such as urban traffic congestion and traffic accidents have become more and more serious. Nowadays, driving is not only concerned about the correct road, but also about road conditions such as congestion and accidents. Paying attention to road conditions means paying attention to travel time and safety. The intelligent transportation system is proposed to effectively solve the above problems. How to obtain effective traffic conditions and share them with people around you has become a topic and direction that everyone is concerned about. Many different methods are used in many fields to explore this issue, such as the application of traffic microblogging platforms, broadcast text me...

AI Technical Summary

Problems solved by technology

Compared with the first method, although this method has improved in cost and coverage, and the equipment is easy to maintain and will not be disturbed by other irrelevant factors such as weather and pedestrians, it still requires a large one-time investment. Accuracy is also limited by map matching techniques

Considering the communication cost, the collection frequency of GPS data of floating vehicles is often low, usually around 15 minutes or 1-5 minutes. However, due to the lack of traffic context information on the server side, GPS data can only be used to screen and filter invalid data. This brings great difficulty to data preprocessing and map matching, and reduces the real-time performance of data while increasing the burden on the server

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