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2717. Enhanced analysis for more sustainable traffic systems through Two-Step-SDP

Invited abstract in session TC-56: Advancing mobility towards sustainable solutions I, stream Transportation.

Tuesday, 12:30-14:00
Room: S04 (building: 101)

Authors (first author is the speaker)

1. Eloisa Macedo
Department of Mechanical Engineering, University of Aveiro
2. Paulo Fernandes
University of Aveiro
3. Jorge Bandeira
University of Aveiro

Abstract

The EMBRACER Project focuses on improving the interconnection with urban and rural areas and achieve seamless intelligent climate-resilient regional and local intermodal mobility. Under this framework, digitalisation and traffic/transport data are essential to promote more sustainable mobility alternatives and satisfy citizens mobility needs. Data-driven knowledge allows for more informed and effective decision-making, both at a strategic and operational level. In this context, data analysis tools play a relevant role. We will focus on the potential of the Two-Step-SDP methodology for analysing vehicle dynamics data and gaining insights regarding traffic-related impacts. The technique is suitable for performing data clustering and dimensionality reduction, has shown superior performance to analogous methodologies, and it is implemented as an open-source tool. In particular, it considers the clustering problem of objects and attributes formulated as nonlinear SDP-based models and, due to their nature, it requires the use of Linear SDP relaxations and an approximation algorithm to obtain their solution. This methodology was applied to different sets of vehicle dynamics data and it revealed to enable a more detailed analysis of the traffic-related impacts. Analising traffic-related data allows policymakers to make evidence-based decisions to improve the sustainability of transport systems and can then, implement targeted interventions to more sustainable mobility solutions.

Keywords

Status: accepted


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