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Sign recognition for autonomous vehicles

A vehicle and character recognition technology, applied in scene recognition, character recognition, vehicle parts, etc., can solve problems such as slowing down the system

Inactive Publication Date: 2018-07-31
FORD GLOBAL TECH LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, higher resolution images also result in intensive calculations, which can slow down the entire system

Method used

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  • Sign recognition for autonomous vehicles
  • Sign recognition for autonomous vehicles
  • Sign recognition for autonomous vehicles

Examples

Experimental program
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Embodiment Construction

[0058] refer to figure 1 , system 100 includes a controller 102 housed within a vehicle. A vehicle may have some or all of the structure and features of any vehicle known in the art, including wheels, a driveline connected to the wheels, an engine connected to the driveline, a steering system, a braking system, and Other systems are known to be included in vehicles.

[0059] As discussed in greater detail herein, the controller 102 may perform autonomous navigation and collision avoidance. Controller 102 may receive one or more outputs from one or more external sensors 104 . For example, one or more cameras 106a may be mounted on the vehicle and output a stream of images received by the controller 102 .

[0060] External sensors 104 may include, for example, ultrasonic sensors 106b, radar (RADAR, radio detection and ranging) sensors 106c, lidar (LIDAR, light detection and ranging) sensors 106d, sonar (SONAR, sound navigation and ranging) sensors 106e, etc. sensor.

[0061...

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PUM

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Abstract

An autonomous vehicle includes both a LIDAR sensor and a camera. A point cloud from the LIDAR sensor is processed to remove points corresponding to a ground plane and points having a reflectivity below a reflectivity threshold. The remaining points are grouped into clusters. Clusters having points satisfying a flatness threshold are then converted into 2D pixel positions in the output of the camera. Regions of interest including these 2D pixel positions are then analyzed to detect and interpret any road signs present.

Description

technical field [0001] The present invention relates to the recognition of road signs by autonomous vehicles. Background technique [0002] Traffic sign recognition (TSR) has been a hot topic in the field of autonomous vehicles. The recognition process includes traffic sign detection and traffic sign recognition. Using state-of-the-art machine learning techniques, more than 99% of traffic sign recognition can be achieved. However, it remains difficult to provide a system that can quickly and accurately locate a marker's position. The accuracy and responsiveness of a camera-based TSR system is very dependent on the resolution of the input image. However, higher resolution images also result in intensive computations, which slow down the entire system. [0003] The systems and methods disclosed herein provide improved methods for traffic sign recognition. Contents of the invention [0004] According to the invention, there is provided a method comprising, by a controlle...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/34G05D1/02G01S17/89G01S17/86G01S17/931G06V30/10
CPCG05D1/0242G05D1/0251G05D1/0255G06V20/582G06V20/58G06V30/153G06V30/287G06V2201/08G01S17/89G01S17/86G01S17/931G06V20/63G06V30/10G05D1/0231B60W2554/00B60W2420/403B60W30/0953B60W2554/20B60W2554/4029B60W2420/408B60W10/04B60W10/18B60W10/20B60W30/09B60W2710/18B60W2710/20B60W2720/10G01S7/4808
Inventor 刘东冉吉内什·J·杰恩
Owner FORD GLOBAL TECH LLC