Work

Improved Map Construction using Subtrajectory Clustering

Year: 2020

Type: conference-paper

Abstract: Map construction is the problem of reconstructing a travel network based on trajectory data of entities travelling on the network. While many map construction algorithms reconstruct the global structure of a network well, local features such as location of crossings and turns are generally harder to reconstruct correctly, in particular for noisy and irregularly sampled data. We demonstrate how subtrajectory clustering can be used to construct maps that capture both the global structure and local features well.

DOI: 10.1145/3423334.3431451

Authors: Kevin Buchin, Maike Buchin, Joachim Gudmundsson, Jorren Hendriks, Erfan Hosseini Sereshgi, Vera Sacristán, Rodrigo I. Silveira, Jorrick Sleijster, Frank Staals, Carola Wenk

Institutions: Eindhoven University of Technology, Ruhr University Bochum, The University of Sydney, Tulane University, Universitat Politècnica de Catalunya, Utrecht University

Language: English

Topic: Data Management and Algorithms

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: gold

Funders: National Science Foundation, Aeronautical Science Foundation of China, Agencia Estatal de Investigación

Awards: G1175115578, G2262748287, G300979063, G3480869486, G425668148, G5080475149, G6769299354, G7084143925, G7894861286, G8130184278, G8684520763

OpenAlex ID: W3097266870

FWCI: 1.25

Cites: 7

Cited by: 12

Related to: 10