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ARCHITECTURES FOR VEHICLE TOLLING

机译:车辆维修体系结构

摘要

Generally discussed herein are systems, devices, and methods for improved automatic toll generation. A system can include one or more cameras positioned to capture images of vehicles passing through a toll station, vehicle detection and classification circuitry to receive an image of a vehicle from the one or more cameras and execute a first machine learning (ML) model to classify the vehicle, axle count circuitry to, in response to receiving data from the vehicle detection and classification circuitry that a vehicle was detected, execute a second ML model to classify a number of axles of the vehicle for determining a toll charge, and toll circuitry to issue the toll charge based on the classified number of axles.
机译:本文一般地讨论了用于改进的自动通行费产生的系统,设备和方法。一种系统可以包括一个或多个照相机,其定位成捕获通过收费站的车辆的图像;车辆检测和分类电路,以从一个或多个照相机接收车辆的图像,并执行第一机器学习(ML)模型以进行分类车辆,车轴计数电路,用于响应于从车辆检测和分类电路接收到检测到车辆的数据,执行第二ML模型以对车辆的车轴数量进行分类,以确定通行费,并且通行费电路根据车桥的分类数量收取通行费。

著录项

  • 公开/公告号US2019378347A1

    专利类型

  • 公开/公告日2019-12-12

    原文格式PDF

  • 申请/专利权人 RAYTHEON COMPANY;

    申请/专利号US201916437315

  • 申请日2019-06-11

  • 分类号G07B15/06;G06N3/08;G06Q20/10;G06K9/32;G08G1/015;G08G1/017;

  • 国家 US

  • 入库时间 2022-08-21 11:25:15

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