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.