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Related Concept Videos

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
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Field Application of Global Positioning System01:28

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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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Design Example: Alignment of a Road Line Using GIS01:17

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Curvilinear Motion: Rectangular Components01:23

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Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
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Relative Motion Analysis using Rotating Axes01:25

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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
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Updated: Aug 2, 2025

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Vehicle Localization in 3D World Coordinates Using Single Camera at Traffic Intersection.

Shenglin Li1, Hwan-Sik Yoon1

  • 1Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA.

Sensors (Basel, Switzerland)
|April 13, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to accurately pinpoint vehicle locations at intersections using a single camera and regression models. Improved vehicle localization enhances traffic signal control, reducing fuel consumption and emissions.

Keywords:
camera calibrationcomputer visionmachine learningobject detectionvehicle localization

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Area of Science:

  • Computer Vision
  • Intelligent Transportation Systems
  • Traffic Engineering

Background:

  • Traffic signal control systems optimize intersection efficiency and reduce vehicle emissions.
  • Adaptive signal control utilizes sensors like cameras, radars, and LiDARs for real-time traffic management.
  • Cameras offer a cost-effective solution for vehicle detection and data acquisition at intersections.

Purpose of the Study:

  • To develop an accurate method for determining vehicle locations at traffic intersections using a single camera.
  • To mitigate localization errors arising from angled camera views.
  • To enhance traffic signal control for improved network-wide energy efficiency and traffic flow.

Main Methods:

  • Utilized the YOLO (You Only Look Once) object detection algorithm to identify vehicles in camera images.
  • Converted image coordinates to world coordinates using camera calibration data.
  • Applied two regression models to correct localization errors in vehicle bounding box centers.

Main Results:

  • Successfully mitigated the significant error between detected and real vehicle centers in world coordinates.
  • Validated the proposed approach using static images and live-streamed traffic video.
  • Demonstrated improved accuracy in vehicle localization for traffic intersection analysis.

Conclusions:

  • The developed approach enhances vehicle localization accuracy at traffic intersections.
  • Accurate localization enables more precise traffic signal control.
  • This contributes to improved overall network-wide energy efficiency and traffic flow.