Submission Deadline: 31 December 2023 (closed) View: 113
Due to their growing populations, large cities are facing acute problems related to the establishment of efficient management of transport flows. As these problems multiply, particularly because of the fast increase of information loads, transportation control centers are in shortage of innovative digital solutions and services for the maintenance of normal traffic. The implementation of Intelligent Transportation Systems (ITSs) has partially fulfilled these requirements. Indeed, in addition to creating smart systems based on advanced transport system models and regulatory frameworks, ITSs are providing road users with safer and optimized commutes that reduce related economic costs and environmental impact. They are also ensuring trains, airports, city transportation facilities, and supply chains run on time and optimally. Nevertheless, the ultimate goals of implementing accurate capacity planning, scheduling, and monitoring of transportation assets are not yet fulfilled. The emergent digital twin technologies have great potentials to accomplish these goals.
A Digital Twin is a virtual replica of a physical object or a system across its life-cycle. It uses real-time data acquired from extensive IoT networks to enable learning, reasoning, and dynamically recalibrating for improved decision making on current and future states of the physical object or system. In the specific domain of transportation and mobility, Digital Twins can be used to optimize the different processes occurring within this field and particularly help with creating the next generation of transportation means and infrastructures for Connected and Autonomous Vehicles. They can also be used to optimize the operations of logistics, scheduling, and capacity planning in train stations, ports or airports, as well as monitoring the progress of transportation assets.
Although the maturity of Digital Twins has reached satisfactory levels, refinement and extensions are still ongoing. The objective of this Special Issue will be to thoroughly investigate the state of the art of applying Digital Twins in the field of smart transportation and mobility and identify the related future directions.
The topics of interests in this Special Issue include, but are not limited to:
· Digital Twins theories, models, and standards
· Digital Twins enabling technologies
· Digital Twins for smart logistics
· Machine Learning for Digital Transportation Twins
· Digital Twins and Blockchain for ITS
· Drivers’ Personal Digital Twins
· Cognitive Digital Twins
· Communication protocols
· Security approaches for transportation Digital Twins
· Digital Twins applications and case-studies for ITS
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