Abstract
This study examines the psychological research that focuses on road safety in Smart Cities as proposed by the Vulnerable Road Users (VRUs) sphere. It takes into account qualities such as VRUs’ personal information, their habits, environmental measurements and things data. With the goal of seeing VRUs as active and proactive actors with differentiated feelings and behaviours, we are committed to integrating the social factors that characterize each VRU into our social machinery. As a result, we will focus on the development of a VRU Social Machine to assess VRUs’ behaviour in order to improve road safety. The formal background will be to use Logic Programming to define its architecture based on a Deep Learning approach to Knowledge Representation and Reasoning, complemented with an Evolutionary approach to Computing.
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Acknowledgments
This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013, being partially supported by a Portuguese doctoral grant, SFRH/BD/130125/2017, issued by FCT in Portugal.
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Fernandes, B., Vicente, H., Ribeiro, J., Analide, C., Neves, J. (2018). Evolutionary Computation on Road Safety. In: de Cos Juez, F., et al. Hybrid Artificial Intelligent Systems. HAIS 2018. Lecture Notes in Computer Science(), vol 10870. Springer, Cham. https://doi.org/10.1007/978-3-319-92639-1_54
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DOI: https://doi.org/10.1007/978-3-319-92639-1_54
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