Data acquisition, visualization and calibration method and system of roadside sensing system

Abstract

The invention provides a data acquisition, visualization and calibration method and system of a roadside sensing system, and the method comprises the steps: a calibration vehicle terminal transmits a package recording starting instruction to a server through UDP communication when the calibration vehicle terminal executes a package recording starting operation, the server forwards a packet recording starting instruction to a to-be-calibrated road end beyond visual range sensing system in a user-defined message protocol, the beyond visual range sensing system starts packet recording operation and records sensing result data of each sensor, when the beyond visual range sensing system starts to execute the packet recording operation, the calibration vehicle immediately starts the packet recording operation and positioning data of integrated navigation on the calibration vehicle is recorded; and according to the recorded sensing result data of each sensor at the roadside end and the absolute positioning data of the calibration vehicle, a laser radar, a millimeter-wave radar and a camera included in the beyond-visual-range sensing system are calibrated by using a calibration algorithm. According to the invention, the data of a plurality of intersection sensing systems can be collected at one time, and the calibration work of each sensor at each intersection is realized.

Description

technical field [0001] The present invention relates to the technical field of roadside perception systems, in particular, to methods and systems for data collection, visualization and calibration of roadside perception systems, and more specifically, to a data collection, visualization and calibration for roadside perception systems Integrated system solution. Background technique [0002] Patent document CN110853393B (application number: 201911176850.6) discloses a method and system for data collection and fusion of intelligent networked vehicle test field. The method includes: step 1, constructing a map of the test field according to the collected static data in the test field static layer; step 2, the roadside dynamic data acquisition module tracks the dynamic targets within the perception range, and generates track data management files under the corresponding label; step 3, obtains the vehicle position through the vehicle end dynamic data acquisition module The data, ...

AI Technical Summary

Problems solved by technology

It can be seen from this that the current calibration scheme for the roadside perception system is very cumbersome, requires high technical level of operators, and has a high time cost

[0004] At the same time, the current calibration algorithms can only calibrate a single sensor, and cannot simultaneously calibrate the lidar, millimeter-wave radar, and camera in the perception system.

[0005] At present, there is no mature and complete roadside sensor automatic calibration system on the market that can simultaneously realize data collection, visualization and automatic calibration of lidar, camera and millimeter-wave radar sensors

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