Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Adaptive road candidates search algorithm for map matching by clustering road segments

Ren, M and Karimi, HA (2013) Adaptive road candidates search algorithm for map matching by clustering road segments. Journal of Navigation, 66 (3). 435 - 447. ISSN 0373-4633

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)

Abstract

Map matching is an important algorithm for any location-based service, especially in navigation and tracking systems and services. Identifying the relevant road segments accurately and efficiently, given positioning data, is the first and most important step in any map matching algorithm. This paper proposes a new approach to searching for road candidates by clustering and then searching road segments through a constructed hierarchical clustering tree, rather than using indexing techniques to query segments within a fixed search window. A binary tree is created based on the hierarchical clustering tree and adaptive searches are conducted to identify candidate road segments given GPS positions. The approach was validated using road maps with different scales and various scenarios in which moving vehicles were located. Both theoretical analysis and experimental results confirm that the proposed approach can efficiently find candidate road segments for map matching. © 2013 The Royal Institute of Navigation.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ren, M
Karimi, HAhkarimi@pitt.eduHKARIMI
Date: 1 May 2013
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Journal of Navigation
Volume: 66
Number: 3
Page Range: 435 - 447
DOI or Unique Handle: 10.1017/s0373463313000076
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISSN: 0373-4633
Date Deposited: 30 Jun 2014 16:55
Last Modified: 02 Feb 2019 16:55
URI: http://d-scholarship.pitt.edu/id/eprint/22044

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com


Actions (login required)

View Item View Item