This research demonstrates improved mobility through AI-driven services for passenger demand prediction, indicating potential for decarbonization.
<ns3:p>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.</ns3:p>
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