Services for Connected, Cooperated, and Automated Mobility based on Big Data and Artificial Intelligence: The SHOW project paradigm

Cooperative, Connected, and Automated Mobility (CCAM) constitutes a viable solution toward sustainable future mobility in order to achieve the target of decarbonization. Artificial Intelligence (AI) and Big Data (BD) have altered several industrial sectors providing novel and affordable solutions that facilitate and improve existing operations in these sectors. Hence, the combination of the CCAM paradigm with AI methodologies based on BD could ever increase the potential benefits of CCAM in the contemporary society. For this reason, three CCAM services, which are based on AI and BD, are introduced in the current research work in order to tackle three well-known issues of mobility such as i) the estimated time of arrival, ii) the passenger demand prediction and iii) the mobility patterns identification. The proposed CCAM services were tested on various pilot sites of the EU-funded SHOW project, thus demonstrating the potential of BD and AI in future mobility services.

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Publication Details

Journal
Open Research Europe
Published
2025-11-27
DOI
https://doi.org/10.12688/openreseurope.18878.2
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Services for Connected, Cooperated, and Automated Mobility based on Big Data and Artificial Intelligence: The SHOW project paradigm

Evangelos Bekiaris, Georgia Ayfantopoulou, Georgios Spanos, Athanasios Sersemis et al.
Open Research Europe
Traffic Prediction and Management Techniques
article

Services for Connected, Cooperated, and Automated Mobility based on Big Data and Artificial Intelligence: The SHOW project paradigm

Evangelos Bekiaris, Georgia Ayfantopoulou, Georgios Spanos, Athanasios Sersemis, Maria Gkemou, Antonios Lalas, Alexandros Siomos, Josep Maria Salanova Grau, Evangelos Antypas, Filipe Rodrigues, Konstantinos Votis, Mathias Niemann Tygesen, Αλέξανδρος Παπαδόπουλος, Carolin Schmidt, Dimitrios Tzovaras
article en

Abstract

Cooperative, Connected, and Automated Mobility (CCAM) constitutes a viable solution toward sustainable future mobility in order to achieve the target of decarbonization. Artificial Intelligence (AI) and Big Data (BD) have altered several industrial sectors providing novel and affordable solutions that facilitate and improve existing operations in these sectors. Hence, the combination of the CCAM paradigm with AI methodologies based on BD could ever increase the potential benefits of CCAM in the contemporary society. For this reason, three CCAM services, which are based on AI and BD, are introduced in the current research work in order to tackle three well-known issues of mobility such as i) the estimated time of arrival, ii) the passenger demand prediction and iii) the mobility patterns identification. The proposed CCAM services were tested on various pilot sites of the EU-funded SHOW project, thus demonstrating the potential of BD and AI in future mobility services.

Open Research EuropeVol. 5
Information Technologies Institute (GR), Centre for Research and Technology Hellas (GR), Technical University of Denmark (DK)
Openalex Percentile: Top 60%
Traffic Prediction and Management Techniques
DOIOpen Access PDFOpenAlex
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