Pedestrian Crossings Could Be Monitored
A team of researchers from the University of Castilla-La Mancha (UCLM) has developed an intelligent surveillance system able to detect aberrant behavior by drivers and people on foot crossing pedestrian crossings and in other urban settings. The study, published this month in the journal Expert Systems with Applications, could be used to penalize incorrect behavior.
“We have developed an intelligence surveillance software and related theoretical model in order to define ‘normality’ in any setting one wishes to monitor, such as a traffic scenario”, David Vallejo, from the ORETO Applied Intelligent Systems research group of the UCLM and co-author of a study published in the latest issue of Expert Systems with Applications, tells SINC.
The study focused on a pedestrian crossing in a two-way street, regulated by a traffic Light. The authors defined ‘normal’ behavior of cars and pedestrians in this setting, in which they can move when the lights are green, but must stop and not cross the safety lines when the lights are red.
The system, working in a similar way to a human monitor, can detect whether the vehicles and pedestrians are moving “normally”. If at any point any of the movements related to these “objects” is not ‘normal’ (driving through a red light, for example), the program recognizes that the behavior differs from the normal framework established.
The supporting architecture underlying the model is a multi-agent artificial intelligence system (made up of software agents that carry out the various tasks involved in monitoring the environment. It has been designed according to standards recommended by the FIPA (Foundation for Intelligent Physical Agents), an international committee working to promote the adoption and diffusion of this kind of technology.
In order to prove the effectiveness of the model, its creators have developed a monitoring tool (OCULUS), which analyses images taken from a real setting. In order to do this, the team members placed a video camera close to their place of work, the Higher School of Information Technology in Ciudad Real.
“In this way we are able to identify any drivers and pedestrians behaving abnormally, meaning the program could be used in order to penalize such behaviors”, says David Vallejo.
The researchers are continuing their work to fine tune the system, and believe it will be possible to use it in future in other situations, for example in analyzing behavior within indoor environments (museums, for example), or in detecting overcrowding.
References: David Vallejo, Javier Albusac, Luis Jim©nez, Carlos González y Juan Moreno. “A cognitive surveillance system for detecting incorrect traffic behaviors”. Expert Systems with Applications 36 (7): 10503-10511, septiembre de 2009.
Image 1: This is a comparison between the reasoning models of the artificial system and that of a theoretical human monitor in a traffic-based setting. Credit: ORETO research group / SINC
Image 2: The OCULUS monitoring tool used to analyze the behavior of vehicles and pedestrians within a traffic-based setting. Credit: ORETO research group / SINC
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