Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

45
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...
45
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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

26
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...
26
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

26
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
26
Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

51
GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
51
Field Application of Global Positioning System01:28

Field Application of Global Positioning System

38
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...
38
GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

47
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
47

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Plasma-modified biodegradable coatings for controlled nitrogen release from urea.

Scientific reports·2026
Same author

LiDAR-Based Long-Term Mapping in Snow-Covered Environments.

Sensors (Basel, Switzerland)·2025
Same author

Emerging challenges of microplastic impacts to ecological health and climate change.

Marine pollution bulletin·2025
Same author

Multi-Robot Path Planning for High-Density Parking Environments Considering Efficiency and Fairness.

Sensors (Basel, Switzerland)·2025
Same author

Changes in organic matter composition during poultry manure composting: A new perspective on compost maturity using DAX resin fractionation and spectroscopic analysis.

Waste management (New York, N.Y.)·2025
Same author

Altered heme metabolism and hemoglobin concentration due to empirical antibiotics-induced gut dysbiosis in preterm infants.

Computational and structural biotechnology journal·2025

Related Experiment Video

Updated: Jun 13, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.2K

Vehicle Localization Using Crowdsourced Data Collected on Urban Roads.

Soohyun Cho1, Woojin Chung1

  • 1Department of Mechanical Engineering, Korea University, Seoul 02841, Republic of Korea.

Sensors (Basel, Switzerland)
|September 14, 2024
PubMed
Summary
This summary is machine-generated.

This study presents a reliable vehicle localization method using crowdsourced data from urban roads. It addresses sensor inaccuracy and complex environments for improved positioning accuracy.

Keywords:
crowdsourced datasimultaneous localization and mappingvehicle localization

More Related Videos

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.3K
Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.5K

Related Experiment Videos

Last Updated: Jun 13, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.2K
Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.3K
Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.5K

Area of Science:

  • Robotics
  • Geomatics Engineering
  • Computer Vision

Background:

  • Vehicle localization is crucial for autonomous driving and road mapping.
  • Crowdsourced data from low-cost sensors offer cost-effective data collection for extensive road networks.
  • Low-cost sensors and urban environments present challenges like sensor inaccuracy and GNSS signal obstruction.

Purpose of the Study:

  • To propose a reliable vehicle localization method for urban roads using crowdsourced data.
  • To address the challenges of high sensor inaccuracy, complex road structures, and environmental changes.
  • To incorporate a reliability assessment for localized vehicle poses.

Main Methods:

  • Utilizing a large volume of crowdsourced vehicle trajectory and road observation data.
  • Developing a localization algorithm robust to inaccurate sensor readings.
  • Integrating partial high-definition (HD) maps to account for environmental changes.
  • Implementing a reliability assessment for the estimated vehicle poses.

Main Results:

  • Demonstrated a reliable vehicle localization method for urban environments.
  • Successfully addressed challenges posed by inaccurate sensor data and complex road structures.
  • Validated the method's performance using real-world data from buses in Seoul, Korea.

Conclusions:

  • The proposed method offers a reliable solution for vehicle localization in urban settings using crowdsourced data.
  • The reliability assessment enhances the trustworthiness of localized vehicle poses.
  • The approach is effective even with data collected significantly after HD map creation, indicating adaptability.