Research Project
1. Context
The urban mobility system can be considered as a complex system whose understanding requires a
perfect mastery of the network of interactions between its components and sub-systems
(infrastructures, information systems, actors, etc.). To ensure better socio-economic integration,
preserve the environment and the social cohesion of travelers, it is urgent to structure existing systems
according to the requirements of sustainable development. Today, in addition to economic, social and
environmental factors, it is also imperative to take into account informational aspects. However, these
requirements make decision-making more complex.
To meet these challenges, transport organizing authorities are gradually moving towards intelligent
transport systems based on the intensive use of ICT (Information and Communication Technologies)
to promote mobility in line with technological and societal changes (Goldman, 2006), thus making ICT
and in particular information systems (IS) an essential component of the transport ecosystem. The
transport information system must store (and manage) data to help travelers better organize their
journey and respond to requests such as: what is the most economical way to get from one place to
another? What is the best combination and how long is the journey? On the other hand, the intelligent
use of the information system makes it possible to identify service congestion and service points of
particular interest and contradictory developments, which are resolved by redefining the physical
system. The intensification of the use of these technologies to develop facilities and solutions adapted
to the needs of the population while preserving resources and the environment and optimizing the
use of existing infrastructure in the context of an agglomeration has highlighted the concept of the "
smart city ".
To meet this need for agility and integration of these technologies, in developed countries a new
approach to the definition of transport systems is being addressed, focusing on the joint deployment
of the physical subsystem (infrastructure and equipment) and the associated information subsystem
(transport information and management technologies). It is known that the physical architecture of a
system allows a better structuring of the definition of the corresponding information system. This can
lead to joint control of development cycles and coordinated management of the related projects, thus
ensuring the relevance of technological choices, a substantial reduction in development costs,
passenger satisfaction and reduced environmental impact. This situation does not yet seem to be
favorably reflected in developing countries, where priority is still given to catching up on infrastructure
delays. In the literature, we now refer to cyber-physical systems.
The term cyber-physical systems (CPS) refers to a new generation of systems with integrated physical
and computing capabilities that can interact with humans in many new ways. In the field of
transportation, these systems are referred to as cyber-physical transportation systems (Monostori L.,
2014). This ability to interact with the physical world and increase its computing, communication and
control capabilities is a key element of future technological developments. Cyber-physical transport
systems enable users to be better informed about routes and service offerings, and to ensure safer,
better coordinated and "smarter" use of transport networks. For example, they aim to increase travel
efficiency, reduce congestion, improve road safety, security and privacy, increase economic growth
and reduce air pollution (Cassandras, 2016, Jeong et al. 2020, Krä, M. et al., 2019). This scientific
revolution provides the basis for a comprehensive understanding of the design, development,
certification, and evolution of cybernetic physical systems in transport systems and other areas such
as energy distribution, health, environmental monitoring, business, commerce, emergency response,
and social activities.
In immature cities and developing countries, in particular, the growing need for passenger and freight
mobility increases the problems of traffic congestion, accidents, and pollution. Chen et al, (2015) in
their work consider that the construction of new road infrastructure alone cannot solve these
problems and propose the implementation of intelligent transport systems. However, the integration
of this new approach based on information systems requires the consideration of new services that
must be grouped and co-operate through information and communication technologies.
2. Main objectives:
In this context, in this research project, we are interested in the design of the integrated intelligent
urban mobility system, considered as a combination of interrelated physical and information
subsystems, having the capacity to allow the mutual control of these subsystems. The main expected
outcome of this work is the proposal of a flexible model to assist in the choice of intelligent urban
mobility systems in the framework of developing countries, taking into account local specificities and
sustainability requirements. Characterization of existing systems will then have to be carried out to
allow better integration of new components (services) and thus reduce its complexity through a study
of interactions. Then, a validation of the results will be done by simulation. Before this, a good review
of the literature on urban mobility systems in general and the case of developing countries in
particular, ontologies, cyber-physical systems, distributed architectures and application development
will have to be studied.
Keywords: Sustainable urban mobility, decision support, ontology, client-server architecture, cyberphysical systems, distributed systems.
References:
Cassandras, C. G. (2016). Smart cities as cyber-physical social systems. Engineering, 2(2), 156-158.
Chen, D., Asplund, F., Östberg, K., Brezhniev, E., & Kharchenko, V. (2015). Towards an Ontology-Based
Approach to Safety Management in Cooperative Intelligent Transportation Systems. In Theory and
Engineering of Complex Systems and Dependability (pp. 107-115). Springer International Publishing.
Giffinger, R. (2015, May). Smart city concepts: Chances and risks of energy-efficient urban
development. In International Conference on Smart Cities and Green ICT Systems (pp. 3-16). Springer
International Publishing.
Goldman, T., & Gorham, R. (2006). Sustainable urban transport: Four innovative directions. Technology
in society, 28(1), 261-273.
Jeong, S., Baek, Y., & Son, S. H. (2020). Component-Based Interactive Framework for Intelligent
Transportation Cyber-Physical Systems. Sensors, 20(1), 264.
Krä, M., Hörbrand, S., & Schilp, J. (2019). Dynamic production control for flexibility in Cyber-Physical
Production Systems using an autonomous transport system. Procedia CIRP, 81, 1160-1165.
Krä, M., Hörbrand, S., & Schilp, J. (2019). Dynamic production control for flexibility in Cyber-Physical
Production Systems using an autonomous transport system. Procedia CIRP, 81, 1160-1165.
Mnasser, H., Gargouri, F., & Abed, M. (2013). Towards an intelligent information system of public
transportation. In Advanced Logistics and Transport (ICALT), 2013 International Conference on (pp.
75-81). IEEE.
Moskolaï J. N., Ngouna, R. H., Hedi K. M., Archimède B., (2019). Ontology-based approach for
complexity management in the design of a sustainable urban mobility system. IEEE International
Conference on Systems, Man and Cybernetics (SMC). October 6-9, 2019, Bari, Italy.
Mfenjou, M. L., Ari, A. A. A., Abdou, W., & Spies, F. (2018). Methodology and trends for an
intelligent transport system in developing countries. Sustainable Computing: Informatics and
Systems, 19, 96-111.