Method, system and device for judging and positioning traffic accident on non-monitoring road section
A technology for traffic accidents and road sections, which is applied in the traffic control system of road vehicles, traffic control system, traffic flow detection, etc., can solve the problems of inconvenient promotion and high cost, and achieve the effect of alleviating peak road pressure and increasing road traffic capacity
Active Publication Date: 2020-12-08
深兰人工智能应用研究院(山东)有限公司
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AI Technical Summary
Problems solved by technology
The former still needs to lay equipment on the complex road network, while the latter needs to install equipment on the vehicle. The two hardware-based solutions are expensive and not easy to promote
Method used
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Embodiment 1
[0028] The invention proposes a method for judging and locating abnormalities in the road section by using the traffic flow and speed data near the monitoring point of the road section.
[0029] Mainly solve two technical problems:
[0030] 1. Feature extraction and diagnosis of the nearest monitoring point
[0031] Based on the existing road network monitoring points and their relative spatial positions, the road network is segmented and modeled; the abnormal conditions of the road sections will be feature extracted and diagnosed by the nearest monitoring points;
[0032] 2. Judgment of abnormal traffic conditions and location of accident points
[0033] Establish corresponding machine learning algorithms to judge whether abnormal conditions affecting traffic occur in the road section, and determine the location of the accident point.
[0034] 1. Road network model
[0035] Based on the road network monitoring points and their relative spatial positions, the road network i...
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The invention discloses a method, a system and a device for judging and positioning a traffic accident in a non-monitoring road section, which specifically comprise the following steps of: dividing aroad network into road sections based on road network monitoring points and relative spatial positions thereof, and monitoring vehicle flow entering the road sections, vehicle speed, vehicle flow leaving the road sections and vehicle speed at two ends of the road sections; performing road section two-way modeling, and learning road information of a specific road section through neural network model training parameters: inputting change vectors of vehicle speeds of monitoring points at two ends at different moments and change vectors of flow at different moments, and standardizing and mapping data of four time sequences to a [0, 1] interval according to the first n moments; and recording the monitoring state at the current moment. According to the method, the monitoring data are adopted torealize judgment and positioning of unmonitored road section accidents.
Description
technical field [0001] The invention belongs to the field of intelligent traffic and relates to a machine learning method for traffic accident diagnosis and positioning. Background technique [0002] With the development of smart cities, road monitoring facilities are becoming more and more complete, and computer vision-based deep learning solutions can quickly capture vehicle accidents within the working range of monitoring equipment. However, the complexity of the road network determines that it is impossible to deploy monitoring equipment in every part of the road. Especially for urban trunk roads, elevated roads, etc., which carry a large number of vehicles during special periods, once a traffic accident occurs, it will directly cause traffic congestion. If the time-series data collected by limited road monitoring equipment can be used to diagnose and locate accidents on non-monitored road sections, it will help the traffic police to quickly intervene in the accident sc...
Claims
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Patent Timeline
Login to View More IPC IPC(8): G08G1/01G08G1/052G08G1/065G06Q50/30G06N3/04G06N3/08
CPCG08G1/0104G08G1/0125G08G1/052G08G1/065G06N3/08G06N3/048G06N3/045G06Q50/40
Inventor 陈海波戴昌志
Owner 深兰人工智能应用研究院(山东)有限公司