Comparison Analysis On Noise Reduction In Gps Trajectories Simplification

Reyes, Gary; Estrada, Vivian

doi:10.18687/laccei2021.1.1.96

Cited by 3 publications

(2 citation statements)

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“…While there are challenges such as scalability and the volume of data present in the processing that can impact the identification objectives, several studies have proposed alternatives to overcome them, such as techniques that deal with data validation to process more compact datasets without impacting the quality or performance of the processing [7][8][9].…”

Section: Related Workmentioning

confidence: 99%

Method for the Identification and Classification of Zones with Vehicular Congestion

Reyes,

Tolozano-Benites,

Lanzarini

et al. 2024

IJGI

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Persistently, urban regions grapple with the ongoing challenge of vehicular traffic, a predicament fueled by the incessant expansion of the population and the rise in the number of vehicles on the roads. The recurring challenge of vehicular congestion casts a negative influence on urban mobility, thereby diminishing the overall quality of life of residents. It is hypothesized that a dynamic clustering method of vehicle trajectory data can provide an accurate and up-to-date representation of real-time traffic behavior. To evaluate this hypothesis, data were collected from three different cities: San Francisco, Rome, and Guayaquil. A dynamic clustering algorithm was applied to identify traffic congestion patterns, and an indicator was applied to identify and evaluate the congestion conditions of the areas. The findings indicate a heightened level of precision and recall in congestion classification when contrasted with an approach relying on static cells.

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Section: Related Workmentioning

confidence: 99%

Method for the Identification and Classification of Zones with Vehicular Congestion

Reyes,

Tolozano-Benites,

Lanzarini

et al. 2024

IJGI

Self Cite

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“…The main objective of noise reduction is the elimination of outliers by correcting the points of the trajectory from an initial state, as the author of this work demonstrates by Reyes et al [51]. For this purpose, the Kalman noise reduction logic is applied, which takes into account the characteristics of the problem to be treated.…”

Section: Noise Reductionmentioning

confidence: 99%

Batch Simplification Algorithm for Trajectories over Road Networks

Reyes,

Estrada,

Tolozano-Benites

et al. 2023

IJGI

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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.

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Batch Simplification Algorithm for Trajectories over Road Networks

Reyes¹,

Estrada²,

Tolozano-Benites³

et al. 2023

Preprint

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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

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Comparison Analysis On Noise Reduction In Gps Trajectories Simplification

Cited by 3 publications

References 0 publications

Method for the Identification and Classification of Zones with Vehicular Congestion

Method for the Identification and Classification of Zones with Vehicular Congestion

Batch Simplification Algorithm for Trajectories over Road Networks

Batch Simplification Algorithm for Trajectories over Road Networks

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