- Version
- Download 31
- File Size 170 KB
- File Count 1
- Create Date May 20, 2021
- Last Updated June 3, 2021
This document constitutes Deliverable D2.1 ‘Use case definition, requirements, metrics definition and expected results’ in the framework of the project titled ‘Revealing fair and actionable knowledge from data to support women’s inclusion in transport systems.’ (Project Acronym: DIAMOND; Grant Agreement No 824326). Differences between men and women in mobility patterns and participation in transport related jobs have been highlighted in several studies and are gaining importance in the society.
The work underlying this Deliverable D2.1 aims to overcome unfairness issues regarding gender in transport, addressing women needs, requirements and expectations in relation to transportation by applying a novel representation of the transport system and its users, named the Inclusion Diamond (ID) and Polyhedral individual (PI) model. The creation of this innovative methodology to address gender questions in the transport system is based on a deep review of the available data and research to identify several dimensions of the transport system in this ID model, named vertexes and layers. Relevant characteristics of the PI (ethnic, gender, age, etc.) are feeding the model showing the influence of individual behavioural patterns both as users and job holders of this transport system. This is a user centred model, with the PI at the core of the ID representation, which will allow to organize data, sources and collection methods in different dimensions of transportation ensuring the generation of high impact measures in better inclusion of women in the transport system both as users and job holders.
The results of this Deliverable D2.1 are the implementation of a more precise definition of women profiles and the translation of these elements in 4 real-world scenarios of the transport system where the ID and PI model was applied, defining the required data, metrics and expected results per each use case along the project life.
These real-world scenarios, or use cases, are: i.) Public transport infrastructure. Railways ii.) Vehicle dynamic control/ADAS, iii.) Vehicle sharing fleet management, iv.) Women recruitment in railways and freight/CSR protocols. This deliverable D2.1 is especially interesting to transport infrastructure designers, policy makers in transportation, managers of transport companies and researchers in the field of gender in transport. Further developments of the project will follow the roadmap stated in this D2.1, focussing on:
- The obtainment of the required data (quantitative and qualitative) identified in this deliverable per each use case (WP3).
- The analysis of this data by using machine learning techniques and an interdisciplinary panel (WP4).
- The obtainment of a hierarchized list of factors or criteria influencing on the inclusion of women in the transport system per each use case which will enable the issue of a list of inclusive measures of women in the transport system, both as users and as a job holders (WP4).
- The obtainment of a list of fairness variables, or KPIs, applicable to each use case against which to compare all the inclusion measures in order to achieve not only inclusive measures but also fair measures (WP2).
- These inclusive and fair measures will be included in a DIAMOND toolbox as guidelines and white papers and auto-diagnosis tools to turn the acquired knowledge into actions (WP5).