Abstract
This paper does in a first step discuss the necessity of a “real-time road safety assessment” capability. Since traditional road safety has mainly been an offline and post-event business, the fundamental question here is that of exploring ways/concepts and technologies for enabling a form of real-time and driver-context-specific road safety assessment before fatal events such as accidents happen. The motivation is evident, as it is well known that “prevention is better than cure”. Concerning “fatal events” this paper also proposes a nuance and an extension of the concept. It does suggest a full range of event categories ranging from “hard fatal events” like a real accident to “soft fatal events” such as stress situation, some abrupt braking or just a lack of ergonomy of certain parts of the road traffic network in time and space. The availability of precious real-time data does in fact open a new research avenue for road safety. Real-time safety assessment that may be coupled to eco-driving considerations will enable a real-time recommender system for driver assistance and/or car navigation.
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Kyamakya, K., Chedjou, J.C., Machot, F.A., Fasih, A. (2012). Enabling a Driver-Specific “Real-Time Road Safety” Assessment through an “Extended Floating Car Data” and Visualization System. In: Unger, H., Kyamaky, K., Kacprzyk, J. (eds) Autonomous Systems: Developments and Trends. Studies in Computational Intelligence, vol 391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24806-1_22
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DOI: https://doi.org/10.1007/978-3-642-24806-1_22
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