Edinburgh Napier University

  Current transport systems do not sufficiently take into account physical and social characteristics of women in the design of products and services, and in fostering women’s employability in the industry. Technologies such as data mining and analytics, together with the use of elicitation techniques to gather and analyse information from different stakeholders, allow the generation of actionable knowledge for addressing gender-specific needs for transport decision-making, planning tools and methods. DIAMOND will exploit such technological advances and innovations, to (i) analyse real-world scenarios where these open issues exist, and (ii) take concrete action, to create a fair and inclusive transport system. DIAMOND’s main goal is to turn data into actionable knowledge with notions of fairness, in order to progress towards an inclusive and efficient transport system. This objective will be achieved by the development of a methodology based on the collection and analysis of disaggregated data, including new sources, analytics and management techniques. Thus this allows to identify, design and evaluate specific measures for fulfilling the needs and expectations of women as users of different transport modes and as jobholders in the sector. The knowledge gathered in the data analysis will then be fed into a toolbox that will provide recommendations on how to achieve fair inclusiveness for women in each of the identified use-cases. Interdisciplinary analysis combining methods from social sciences and computer science will contribute to fairness of the model and its results (i.e. condition of being free from bias or injustice). To proof actionability, this project will make concrete advances in four real-world scenarios (use-cases) where inclusiveness is currently a central issue: 1.- railways and public multimodal transport, 2.- Vehicle Dynamics control towards autonomous driving, 3.- vehicle sharing and 4.- corporate social responsibility and employment
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 824326 and is in collaboration with 13 partners, the project is led by Fundacio Eurecat (EUT)