A cognitive surveillance system for detecting incorrect traffic behaviors

Authors:
David Vallejo;Javier Albusac;Luis Jimenez;Carlos Gonzalez;Juan Moreno
Affiliations:
School of Computer Science, Department of Information Technologies and Systems, Paseo de la Universidad 4, 13071 Ciudad Real, Ciudad Real, Oreto Research Group, University of Castilla-la Mancha, S ...;School of Computer Science, Department of Information Technologies and Systems, Paseo de la Universidad 4, 13071 Ciudad Real, Ciudad Real, Oreto Research Group, University of Castilla-la Mancha, S ...;School of Computer Science, Department of Information Technologies and Systems, Paseo de la Universidad 4, 13071 Ciudad Real, Ciudad Real, Oreto Research Group, University of Castilla-la Mancha, S ...;School of Computer Science, Department of Information Technologies and Systems, Paseo de la Universidad 4, 13071 Ciudad Real, Ciudad Real, Oreto Research Group, University of Castilla-la Mancha, S ...;School of Technical Engineering, Avda, Carlos III s/n, Toledo, Oreto Research Group, University of Castilla-la Mancha, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

Traffic accidents, in which pedestrians are often involved, injure and kill many people yearly. One critical scene is the crosswalk, an important knocking down source due to both drivers' and pedestrians' incorrect behaviors. In this work, we propose a novel approach to detect and sanction these drivers' abnormal behaviors. The multi-agent system paradigm embodies this approach, together with the use of FIPA standards, and a traffic ontology formalizes the domain knowledge. Besides developing the architecture, a simulator is also presented for generating random situations in the crosswalk scene. This system involves a first approximation in relation to the control of drivers' abnormal behaviors in a crosswalk controlled by a traffic light, obtaining a high-scalable and flexible system which can be adapted to other domains.