Relationships of Compression Ratio and Error in Trajectory Simplification Algorithms

Reyes, Gary; Maquilón, Víctor; Estrada, Vivian

doi:10.1007/978-3-030-88262-4_10

Cited by 3 publications

(1 citation statement)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The author of the present work considers that it is the best option of the four algorithms analyzed, since it reported the second best compression ratio, the second best margin of error, considering that it is the only one that performs a spatio-temporal analysis and that the applicability of the present work is not based on the analysis of real-time trajectories, which are more focused on obtaining better times. The used metrics to perform the measurements to the "GR Simplification" algorithm, considering the application scenario in road networks and disconnected (batch) environments, are the compression ratio rate and the margin of error [28,57,58]. For the comparison of the "GR Simplification" algorithm and TD-TR, the margin of error formula found in this paper [59] is used.…”

Section: Initial Diagnostics Of Batch Gps Trajectory Simplification A...mentioning

confidence: 99%

Batch Simplification Algorithm for Trajectories over Road Networks

Reyes,

Estrada,

Tolozano-Benites

et al. 2023

IJGI

Self Cite

View full text Add to dashboard Cite

The steady increase in data generation by GPS systems poses storage challenges. Previous studies show the need to address trajectory compression. The demand for accuracy and the magnitude of data require effective compression strategies to reduce storage. It is posited that the combination of TD-TR simplification, Kalman noise reduction, and analysis of road network information will improve the compression ratio and margin of error. The GR algorithm is developed, integrating noise reduction and path compression techniques. Experiments are applied with trajectory data sets collected in the cities of California and Beijing. The GR algorithm outperforms similar algorithms in compression ratio and margin of error, improving storage efficiency by up to 89.090%. The combination of proposed techniques presents an efficient solution for GPS trajectory compression, allowing to improve storage in trajectory analysis applications.

show abstract

Section: Initial Diagnostics Of Batch Gps Trajectory Simplification A...mentioning

confidence: 99%

Batch Simplification Algorithm for Trajectories over Road Networks

Reyes,

Estrada,

Tolozano-Benites

et al. 2023

IJGI

Self Cite

View full text Add to dashboard Cite

show abstract

Data Stream Processing Method for Clustering of Trajectories

Reyes

Lanzarini

Estrebou

et al. 2022

Communications in Computer and Information Science

View full text Add to dashboard Cite

Batch Simplification Algorithm for Trajectories over Road Networks

Reyes¹,

Estrada²,

Tolozano-Benites³

et al. 2023

Preprint

View full text Add to dashboard Cite

The volume of vehicular traffic in large cities has increased in recent years, the devices that collect vehicular GPS data such as cameras, GPS receivers and others generate millions of records at every instant of time generating problems in processing and storage of these data which becomes important for researchers. Intelligent Transportation Systems perform vehicle monitoring and control by collecting GPS trajectories, this large volume of information is necessary to have an optimal storage process. Its processing by means of compression techniques and simplification algorithms allow to reduce the necessary storage space. This paper presents a GPS trajectory simplification algorithm that considers noise reduction, point simplification and analysis of road network information. The results obtained on two data sets from the cities of California and Beijing are satisfactory, achieving a higher compression ratio without affecting data quality

show abstract

Relationships of Compression Ratio and Error in Trajectory Simplification Algorithms

Cited by 3 publications

References 22 publications

Batch Simplification Algorithm for Trajectories over Road Networks

Batch Simplification Algorithm for Trajectories over Road Networks

Data Stream Processing Method for Clustering of Trajectories

Batch Simplification Algorithm for Trajectories over Road Networks

Contact Info

Product

Resources

About