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 and Mutaz H. H. Khairi
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Ali Louati: Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
Hassen Louati: SMART Lab, Higher Institute of Management, University of Tunis, Tunis 2000, Tunisia
Elham Kariri: Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
Wafa Neifar: ANLP-RG, MIRACL Laboratory, University of Sfax, Sfax 3018, Tunisia
Mohammed A. Farahat: Computer Science Department, Higher Future Institute for Specialized Technological Studies, Cairo 3044, Egypt
Heba M. El-Hoseny: Computer Science Department, Higher Future Institute for Specialized Technological Studies, Cairo 3044, Egypt
Mohamed K. Hassan: Faculty of Telecommunications Engineering, Future University, Khartoum 10553, Sudan
Mutaz H. H. Khairi: Faculty of Engineering, Future University, Khartoum 10553, Sudan

Sustainability, 2024, vol. 16, issue 4, 1-16

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.

Keywords: sustainable urban mobility; cloud-based collaboration; road information discovery; Kalman Filter; Gaussian process (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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