An Ontological Framework for Implementing Soft Mobility Knowledge Model in Urban Areas

This study is a doctoral dissertation.. It contributes to the field of urban planning, design, and policy, particularly in the field of mobility and transportation. Transport experts and governing institutions are frequently tasked with conducting theoretical and empirical research in order to develop and improve the performance of their national transport systems. Mobility planning is a broad field that relies on data from multiple scientific disciplines. When planning mobility, it is important to adopt a holistic perspective, one that considers different aspects related to soft mobility. Today, soft mobility is an essential form of sustainable urban mobility. It saves energy, improves health, provides affordable and flexible transport options, decreases traffic congestion, improves interpersonal relations and social inclusion, enhances accessibility, regenerates public space, supports tourism, and reduces harmful emissions. For soft mobility to be effective in an urban setting, it must be interconnected and isotopic. In addition, to manage urban elements and soft mobility system elements, such as public costs of infrastructure, public costs of maintenance, possible public incentives for electrical bikes or scooters, private costs of purchasing means of mobility, and private costs of time, a modeling process or decision support system is required. For this purpose, ontologies are well-suited to addressing the challenges of system complexity and loosely organized data. The use of ontology development approaches focuses primarily on defining machine-interpretable concepts and the relationships between these concepts in their domain. It provides substantial benefits to numerous scientific disciplines, including mobility and transportation. In addition, others pursue the objectives of creating and sharing domain concepts, allowing domain experts to reuse domain knowledge, enabling domain researchers to analyze domain knowledge and express domain assumptions, and assisting individuals and software agents in understanding the structure of domain concepts. Nonetheless, there is a lack of research interest in the mobility planning domain of soft mobility. A handful of developing ontological projects pertaining to soft mobility have been published since 2002. However, an exhaustive and precise ontology is needed for the modeling process and for decision support systems. Thus, this study used ontology development approaches to create a knowledge model for soft mobility in Semantic Web to provide explicit, simplified, and essential information for planners, engineers, and operators in mobility and transportation fields at all levels of government and administration to make sustainable urban mobility decisions. In terms of scope, this study focused on fundamental elements of spatial relationship, consisting of soft mobility infrastructure, networks, modes, and flows. Its focus is only on walking and cycling. The following phases were planned and implemented: objective and scope definition, information collection and extraction, initial structuring, formalization, deployment, and evaluation. In addition, a Simple knowledge-engineering methodology based on Protégé was selected, a widely cited method for ontology development. In the end, a comprehensive soft mobility knowledge model was developed as a heavyweight ontology in OWL. A multitude of its fundamental spatial elements concepts and instances were defined, and a few were clarified in terms of defining how they behave. Finally, the model also provides a graphical representation of soft mobility and automatic access to soft mobility ontology-based data. Those interested in urban planning, design, and policy, particularly mobility and transportation, will profit from this study.