Sustainable Urban Mobility for Road Information Discovery-Based Cloud Collaboration and Gaussian Processes

Ali Louati; Hassen Louati; Elham Kariri; Wafa Neifar; Mohammed A. Farahat; Heba M. El-Hoseny; Mohamed K. Hassan; Mutaz H.H. Khairi

doi:10.3390/su16041688

Sustainable Urban Mobility for Road Information Discovery-Based Cloud Collaboration and Gaussian Processes

Ali Louati, Hassen Louati, Elham Kariri, Wafa Neifar, Mohammed A. Farahat, Heba M. El-Hoseny, Mohamed K. Hassan, Mutaz H.H. Khairi

Information Systems

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

A novel cloud-based collaborative estimation framework for traffic management, utilizing a Gaussian Process Regression approach is introduced in this work. Central to addressing contemporary challenges in sustainable transportation, the framework is engineered to enhance traffic flow efficiency, reduce vehicular emissions, and support the maintenance of urban infrastructure. By leveraging real-time data from Priority Vehicles (PVs), the system optimizes road usage and condition assessments, contributing significantly to environmental sustainability in urban transport. The adoption of advanced data analysis techniques not only improves accuracy in traffic and road condition predictions but also aligns with global efforts to transition towards more eco-friendly transportation systems. This research, therefore, provides a pivotal step towards realizing efficient, sustainable urban mobility solutions.

Original language	English
Article number	1688
Journal	Sustainability (Switzerland)
Volume	16
Issue number	4
DOIs	https://doi.org/10.3390/su16041688
State	Published - Feb 2024

Keywords

Gaussian process
Kalman Filter
cloud-based collaboration
road information discovery
sustainable urban mobility

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/su16041688

Cite this

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title = "Sustainable Urban Mobility for Road Information Discovery-Based Cloud Collaboration and Gaussian Processes",

abstract = "A novel cloud-based collaborative estimation framework for traffic management, utilizing a Gaussian Process Regression approach is introduced in this work. Central to addressing contemporary challenges in sustainable transportation, the framework is engineered to enhance traffic flow efficiency, reduce vehicular emissions, and support the maintenance of urban infrastructure. By leveraging real-time data from Priority Vehicles (PVs), the system optimizes road usage and condition assessments, contributing significantly to environmental sustainability in urban transport. The adoption of advanced data analysis techniques not only improves accuracy in traffic and road condition predictions but also aligns with global efforts to transition towards more eco-friendly transportation systems. This research, therefore, provides a pivotal step towards realizing efficient, sustainable urban mobility solutions.",

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volume = "16",

journal = "Sustainability (Switzerland)",

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AU - Louati, Ali

AU - Louati, Hassen

AU - Kariri, Elham

AU - Neifar, Wafa

AU - Farahat, Mohammed A.

AU - El-Hoseny, Heba M.

AU - Hassan, Mohamed K.

AU - Khairi, Mutaz H.H.

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AB - A novel cloud-based collaborative estimation framework for traffic management, utilizing a Gaussian Process Regression approach is introduced in this work. Central to addressing contemporary challenges in sustainable transportation, the framework is engineered to enhance traffic flow efficiency, reduce vehicular emissions, and support the maintenance of urban infrastructure. By leveraging real-time data from Priority Vehicles (PVs), the system optimizes road usage and condition assessments, contributing significantly to environmental sustainability in urban transport. The adoption of advanced data analysis techniques not only improves accuracy in traffic and road condition predictions but also aligns with global efforts to transition towards more eco-friendly transportation systems. This research, therefore, provides a pivotal step towards realizing efficient, sustainable urban mobility solutions.

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KW - road information discovery

KW - sustainable urban mobility

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Sustainable Urban Mobility for Road Information Discovery-Based Cloud Collaboration and Gaussian Processes

Abstract

Keywords

UN SDGs

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