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Vehicle association method and device, roadside equipment and cloud control platform

A vehicle and average length technology, which is applied in the field of intelligent transportation, devices, vehicle association methods, roadside equipment and cloud control platforms, can solve the problems of inability to associate images and low association success rate, so as to prevent false association and improve association The effect on success rate

Pending Publication Date: 2021-03-16
APOLLO INTELLIGENT CONNECTIVITY (BEIJING) TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Traditional correlation methods are mostly based on single-frame images, but single-frame images have limitations and cannot accurately correlate images collected from different observation points, and the success rate of correlation is low

Method used

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  • Vehicle association method and device, roadside equipment and cloud control platform
  • Vehicle association method and device, roadside equipment and cloud control platform
  • Vehicle association method and device, roadside equipment and cloud control platform

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] figure 1 It is a schematic flow chart of the first vehicle association method provided by the embodiment of this application. The method can be executed by a vehicle association device or electronic equipment or roadside equipment. The device, electronic equipment or roadside equipment can be implemented by software and / or hardware In this way, the device or electronic equipment or roadside equipment can be integrated in any intelligent equipment with network communication function. Such as figure 1 As shown, the vehicle association method may include the following steps:

[0035] S101. For each observation point, collect an image of the current vehicle running on the road according to a preset period.

[0036] In this step, for each observation point, the electronic device may collect images of the current vehicle running on the road according to a preset period. The observation points in this application may be various types of image acquisition devices, such as ca...

Embodiment 2

[0045] figure 2 It is a second schematic flowchart of the vehicle association method provided by the embodiment of the present application. Such as figure 2 As shown, the vehicle association method may include the following steps:

[0046] S201. For each observation point, collect an image of the current vehicle running on the road according to a preset period.

[0047] S202. Based on the images collected by each observation point within a preset time period, determine the current position of the vehicle when each observation point collects each image.

[0048] In this step, the electronic device may determine the current position of the vehicle at each observation point when each image is collected based on the images collected by each observation point within a preset time period. Specifically, the electronic device can identify the images collected by each observation point within a preset time period, for example, the electronic device can input the images collected b...

Embodiment 3

[0056] image 3 It is a schematic flowchart of the third vehicle association method provided by the embodiment of the present application. Such as image 3 As shown, the vehicle association method may include the following steps:

[0057] S301. For each observation point, collect an image of the current vehicle running on the road according to a preset period.

[0058] S302. Determine the original observation sequence of each observation point relative to the current vehicle based on the images collected by each observation point within a preset time period.

[0059] S303. Based on the original observation sequence of each observation point for the current vehicle, determine a target observation sequence for each observation relative to the current vehicle.

[0060] In this step, the electronic device may determine the target observation sequence of each observation relative to the current vehicle based on the original observation sequence of each observation point for the ...

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Abstract

The invention discloses a vehicle association method and device, roadside equipment and a cloud control platform, and relates to the technical field of artificial intelligence, in particular to the field of intelligent transportation. The specific implementation scheme is as follows: for each observation point, acquiring an image of a current vehicle running on a road according to a preset period;determining an original observation sequence of each observation point relative to the current vehicle based on the image acquired by each observation point in the preset time period; determining a target observation sequence of each observation relative to the current vehicle based on the original observation sequence of each observation point for the current vehicle; and based on the target observation sequence of each observation relative to the current vehicle, detecting whether the current vehicles observed at every two observation points are the same vehicle or not. According to the invention, wrong association caused by single-frame image abnormity can be effectively prevented, so that the association success rate can be improved.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, further relates to intelligent transportation technology, and in particular to a vehicle association method, device, roadside equipment and cloud control platform. Background technique [0002] Vehicle association is a core topic of today's intelligent transportation and related technologies. In the real environment, only relying on a single observation point cannot accurately obtain all the information of the vehicle to be observed. Different observation points collect different information in different directions and angles. Therefore, it is extremely necessary to combine the data of the same vehicle obtained from different observation points to obtain high-precision information of a vehicle in various directions or angles. [0003] Traditional correlation methods are mostly based on single-frame images, but single-frame images have limitations, and cannot accurately ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/584G06V20/588G06F18/22G08G1/0116G08G1/04G06V20/54G08G1/0175G06V10/74G06V10/761G06T7/292G06T2207/30236G06T2207/30241G06T7/70G06T7/20G06T2207/10016G06V2201/08
Inventor 曹获
Owner APOLLO INTELLIGENT CONNECTIVITY (BEIJING) TECH CO LTD
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