Road traffic operation state real-time sensing method based on social network information

Abstract

The invention belongs to the technical field of road traffic operation state real-time sensing and discloses a road traffic running state real-time sensing method based on social network information,which comprises the following steps of automatically acquiring, classifying and extracting multi-angle effective traffic information in a social network platform by using a web crawler technology, screening, analyzing and predicting, establishing an end-to-end self-learning model, and performing visual labeling on a map; learning and predicting future data from past data based on deep learning, and feeding back the predicted future data to a social network for users to share traffic information in real time. The system is not limited in spatial distribution, does not need to arrange and maintain ground sensing equipment, has obvious economic advantages, can effectively capture sudden traffic incidents, traffic incidents at specific places, temporary traffic control, newly added traffic restrictions and traffic environment information, provides quick response signals for related management departments, and provides travel decision basis for residents.

Description

technical field [0001] The invention belongs to the technical field of real-time perception of road traffic operation status, and in particular relates to a method for real-time perception of road traffic operation status based on social network information. Background technique [0002] At present, the closest existing technologies include technologies such as sensors, WSN, RFID, location perception, parking lot perception, and road and bridge perception, as well as structured and non-physical systems such as GPS, location, coils, video, and road networks applied to vehicles. The storage and processing of structured massive data is already very mature, that is, the technical foundation is already established in data storage and analysis. In terms of transmission, there are short-distance transmissions and 3G and 4G long-distance transmissions, which make the transmission of large data volumes fast and large in volume, which also has the current foundation. [0003] With th...

AI Technical Summary

Problems solved by technology

[0010] The data collected by traffic detection equipment in the prior art does not contain information from more angles, and the spatial distribution is limited. It is necessary to deploy and maintain ground sensing equipment, and the economic cost is high. On the other hand, the existing guidance information cannot provide travellers. The possible duration of the event does not have a clear guiding effect on the travel of travelers

And it is not conducive to the timely response of the traffic management department to sudden traffic incidents

The real-time perception method of road traffic operation state in the prior art cannot share real-time information of traffic events, cannot match different road traffic operation states, and visually mark on the map, resulting in slow reflection of road traffic change information and poor effect

Moreover, traditional traffic detection equipment relies on hardware terminals such as sensors arranged in a large area, which inevitably exposes the limitations of data terminal collection

Existing technologies are difficult to effectively capture sudden traffic incidents, traffic incidents at specific locations, temporary traffic control, new traffic restrictions and traffic environment information

The existing technology lacks clear information on the time of accident handling, and the information does not have a clear guiding role for travelers

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