1.

Record Nr.

UNINA9910299664403321

Autore

Feng Jun

Titolo

Index and Query Methods in Road Networks / / by Jun Feng, Toyohide Watanabe

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015

ISBN

3-319-10789-5

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (169 p.)

Collana

Smart Innovation, Systems and Technologies, , 2190-3026 ; ; 29

Disciplina

006.3

620

629.2

658.5

Soggetti

Computational intelligence

Industrial Management

Automotive engineering

Computational Intelligence

Automotive Engineering

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Introduction -- Index Techniques -- Road Network Model -- Index in Road Network -- Query in Road Network -- The Trend of Development.

Sommario/riassunto

This book presents the index and query techniques on road network and moving objects which are limited to road network. Here, the road network of non-Euclidean space has its unique characteristics such that two moving objects may be very close in a straight line distance. The index used in two-dimensional Euclidean space is not always appropriate for moving objects on road network. Therefore, the index structure needs to be improved in order to obtain suitable indexing methods, explore the shortest path and acquire nearest neighbor query and aggregation query methods under the new index structures. Chapter 1 of this book introduces the present situation of intelligent traffic and index in road network, Chapter 2 introduces the relevant existing spatial indexing methods. Chapter 3-5 focus on several issues of road network and query, they involves: traffic road network models



(see Chapter 3), index structures (see Chapter 4) and aggregate query methods (see Chapter 5). Finally, in Chapter 6, the book briefly describes the applications and the development of intelligent transportation in the future.