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Distance Measurements by Taping

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Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
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Sight distance on vertical curves is critical in roadway design. It ensures drivers can see far enough ahead to identify and respond to hazards effectively. This directly impacts safety, driver comfort, and the overall efficiency of the transportation network.Vertical curves are classified into crest and sag curves based on their geometry. For crest curves, sight distance is determined by the line of sight between a driver's eye and a small object on the road's surface. Design parameters for...
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Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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Design Example: Measuring Distance Between Two Points with Obstructions01:10

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When measuring distances in areas with physical obstructions, such as a lake in a field, surveyors must employ techniques to calculate accurate lengths without direct line measurements. One effective method is the offset technique, which allows for precise distance estimation over inaccessible stretches.In this scenario, a surveyor must measure a side of an area that crosses a lake. Since the measuring tape cannot span the lake, the surveyor begins by establishing a baseline that aligns with...
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Distance Corrections01:15

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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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Train Distance Estimation for Virtual Coupling Based on Monocular Vision.

Yang Hao1,2, Tao Tang1, Chunhai Gao2

  • 1School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China.

Sensors (Basel, Switzerland)
|February 24, 2024
PubMed
Summary
This summary is machine-generated.

A new vision-based system accurately estimates train distances for virtual coupling (VC) in urban rail transit. This method enhances safety by providing a reliable backup to communication-dependent VC operations.

Keywords:
autonomous drivingmonocular visionobject detectionurban rail transit

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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Urban Rail Transit Engineering

Background:

  • Virtual coupling (VC) in urban rail transit offers operational flexibility but relies on train-to-train communication for distance measurement.
  • Communication malfunctions in VC systems pose significant safety risks due to potential distance miscalculations.

Purpose of the Study:

  • To develop and validate a robust distance-estimation framework for virtual coupling using monocular vision.
  • To enhance the safety and reliability of virtual coupling operations by providing a communication-independent distance measurement solution.

Main Methods:

  • An object-detection neural network with an enhanced feature pyramid, neighbor area labeling, and semantic filtering was employed to extract key structural features of the target train.
  • A multi-feature optimization process was utilized to accurately estimate the distance between coupled train sets.

Main Results:

  • The proposed monocular vision framework achieved distance estimations with an absolute error below 1 meter for train separations between 20m and 100m.
  • A relative error of less than 1.5% was recorded, demonstrating high precision in distance measurement.
  • Experimental validation was successfully conducted on Beijing Subway Line 11.

Conclusions:

  • The monocular vision-based distance estimation framework offers a reliable backup for communication-dependent virtual coupling systems.
  • This technology can significantly improve the safety and efficiency of flexible train operations in urban rail transit.