A method and device for collecting multi-source information in a vehicle-road collaborative environment

Abstract

The invention provides a multisource information acquisition method under the vehicle-road cooperation environment and a device thereof. The vehicle operation condition and roadside traffic equipment operation information are respectively acquired, and instructions and data are transmitted through a vehicle-road communication device so that the vehicle operation state and the traffic state can be comprehensively acquired. The vehicle operation state mainly includes vehicle state diagnosis and driving behavior analysis based on vehicle-mounted bus interface original data, and the vehicle historical data and other vehicle data and roadside information near the locating point are combined by the analysis method so that the judgment accuracy can be enhanced. The traffic state includes multisource information of roadside signal devices and intelligent equipment, deep fusion is performed based on the data of the vehicle-mounted terminal and the roadside terminal and the roadside terminal automatically acquires and summarizes the operating vehicle-mounted terminal data according to the designed method so that the data types can be enriched, the data accuracy can be enhanced and the data processing difficulty and the network data volume can be reduced in comparison with the conventional probe vehicle method, and the technical advantages of traffic analysis and vehicle-road cooperation can be fully combined.

Description

technical field [0001] The invention belongs to the field of information fusion / traffic evaluation, and in particular relates to a vehicle-mounted device capable of collecting vehicle operating condition data through an OBD interface, and uploading the data to roadside devices for traffic evaluation through a vehicle-road communication module. Background technique [0002] The increasingly prominent problem of traffic congestion has seriously restricted the development of cities. Since the urban road network is often in a state of oversaturation during the morning and evening peak hours, the inconvenience of motor vehicles has become a major problem that plagues residents' lives. However, some research results show that the traffic capacity of the current urban road network still has great potential for improvement. In addition to unreasonable road planning and signal timing, the lack of understanding of the real-time conditions of the regional road network by the traffic con...

AI Technical Summary

Problems solved by technology

[0005] In the existing traffic detection technology, the data volume of the fixed detector is not continuous on the road section, and the data of the same vehicle on the two intersection detectors cannot be automatically matched, which leads to difficulties in data processing when analyzing and evaluating the entire road network. situation, and the detector has a short service life and is easily damaged. Although traditional mobile detectors such as floating vehicles can provide complete path information for each vehicle, the amount of data they can provide is too small, and the accuracy of GPS and mobile networks is relatively low. Low areas are prone to data loss

The existing vehicle-road coordination technology, because the relevant standards have not yet been unified, the technology needs to be further matured. At present, the application research based on this technology is mostly in the laboratory and test field stage, and correspondingly lacks corresponding service support. The largest The problem lies in equipment coverage and real-time communication. If there is no high vehicle-road coordination equipment coverage support, it will be difficult to make a unified planning arrangement, and the communication indicators of the existing technology are still difficult for real-time collaborative control.

Existing vehicle behavior evaluation and road network status evaluation often use external sensors to judge the stability and comfort of vehicles and the congestion status of road sections. However, this indirect data collection method itself has certain errors, and it will affect the evaluation results. The lack of handling of vehicle and road network emergencies further leads to the reduction of evaluation accuracy

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