Automated Object Behavioral Feature Extraction for Potential Risk Analysis based on Video Sensor

by   Byeongjoon Noh, et al.

Pedestrians are exposed to risk of death or serious injuries on roads, especially unsignalized crosswalks, for a variety of reasons. To date, an extensive variety of studies have reported on vision based traffic safety system. However, many studies required manual inspection of the volumes of traffic video to reliably obtain traffic related objects behavioral factors. In this paper, we propose an automated and simpler system for effectively extracting object behavioral features from video sensors deployed on the road. We conduct basic statistical analysis on these features, and show how they can be useful for monitoring the traffic behavior on the road. We confirm the feasibility of the proposed system by applying our prototype to two unsignalized crosswalks in Osan city, South Korea. To conclude, we compare behaviors of vehicles and pedestrians in those two areas by simple statistical analysis. This study demonstrates the potential for a network of connected video sensors to provide actionable data for smart cities to improve pedestrian safety in dangerous road environments.



page 2


Vision based Pedestrian Potential Risk Analysis based on Automated Behavior Feature Extraction for Smart and Safe City

Despite recent advances in vehicle safety technologies, road traffic acc...

Analyzing vehicle pedestrian interactions combining data cube structure and predictive collision risk estimation model

Traffic accidents are a threat to human lives, particularly pedestrians ...

Datacentric analysis to reduce pedestrians accidents: A case study in Colombia

Since 2012, in a case-study in Bucaramanga-Colombia, 179 pedestrians die...

Where are the Dangerous Intersections for Pedestrians and Cyclists: A Colocation-Based Approach

Pedestrians and cyclists are vulnerable road users. They are at greater ...

Explainable, automated urban interventions to improve pedestrian and vehicle safety

At the moment, urban mobility research and governmental initiatives are ...

ORCLSim: A System Architecture for Studying Bicyclist and Pedestrian Physiological Behavior Through Immersive Virtual Environments

Injuries and fatalities for vulnerable road users, especially bicyclists...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.