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Proceedings ArticleDOI

Q-factor map matching method using adaptive fuzzy network

Sinn Kim, +1 more
- Vol. 2, pp 628-633
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TLDR
In this paper, a novel map matching method is proposed that uses a digital road map to correct the position error in hybrid algorithms and is verified by the real road experiments.
Abstract
Many hybrid algorithms which estimate car's position and velocity from GPS signals and INS signals suffer from the unknown GPS noise characteristics such as S/A noise. The unknown characteristics make it impossible to remove the noise completely. As a result, the estimated position information from the hybrid algorithms will be contaminated with undesirable position errors. It is very desirable and effective to use a digital road map to correct the position error, which is known as a map matching method. In this paper, a novel map matching method is proposed. The effectiveness of this algorithm is verified by the real road experiments. For experimental testing, a car navigation system is built with a DSP chip. It uses one GPS receiver, one vehicle speed sensor and one vertical gyroscope.

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Citations
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Fuzzy Logic Based-Map Matching Algorithm for Vehicle Navigation System in Urban Canyons

S. Syed, +1 more
TL;DR: Fuzzy logic can be applied effectively to map match the output from a HS GPS receiver in urban canyons because of its inherent tolerance to imprecise inputs.
Journal ArticleDOI

Adaptive fuzzy-network-based C-measure map-matching algorithm for car navigation system

TL;DR: A novel adaptive-fuzzy-network-based C-measure algorithm is proposed, which can find the exact road on which a car moves and is easy to calculate, and calculation time does not increase exponentially with the increase of junctions.
Proceedings ArticleDOI

An improved map-matching algorithm used in vehicle navigation system

TL;DR: Kalman filtering and Dempster-Shafer (D-S) theory of evidence are introduced into the improved map-matching algorithm, and it is found to produce better results.
Journal ArticleDOI

A weight-based map-matching algorithm for vehicle navigation in complex urban networks

TL;DR: The most important feature of the algorithm is that the high correct segment identification percentage achieved in urban areas is through a simple and efficient weight-based method that does not depend on any additional data or positioning sensors other than digital road network and GPS.
Journal ArticleDOI

A fuzzy logic map matching for wheelchair navigation

TL;DR: A fuzzy logic-based algorithm is applied to effectively perform matching wheelchair movements on sidewalks to overcome difficulties in tracking wheelchairs in urban areas due to poor satellite availability.
References
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Book

Kalman Filtering: Theory and Practice

TL;DR: This paper presents a meta-modelling framework for Matrix Refresher that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of manually refreshing the Matrix.
Journal ArticleDOI

Structural properties and classification of kinematic and dynamic models of wheeled mobile robots

TL;DR: The structure of the kinematic and dynamic models of wheeled mobile robots is analyzed and it is shown that, for a large class of possible configurations, they can be classified into five types, characterized by generic structures of the model equations.
Journal ArticleDOI

Inertial navigation systems for mobile robots

TL;DR: A low-cost solid-state inertial navigation system for mobile robotics applications is described and error models for the inertial sensors are generated and included in an extended Kalman filter for estimating the position and orientation of a moving robot vehicle.

Development of a map matching algorithm for car navigation system using fuzzy q-factor algorithm

S Kim Kim
TL;DR: A new map matching method is suggested named as Q-factor algorithm, which can exactly give the position of a car on a road, which is very easy to calculate, and calculations will not exponentially increase with the increase in the number of junctions.

A study on the correction of positioning accuracy of car navigation system and map-matching algorithm

B-C Lee
TL;DR: This paper considers the cause of various errors like datum, projection, local coordinate system and the map matching algorithm using fuzzy logic that can be used to reconcile inaccurate locational data with an inaccurate digital map.
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