EFFECTIVENESS ENHANCEMENT OF TRAFFIC CAMERAS BASED ON VEHICLES' AVERAGE SPEED CALCULATION

The analysis of calculating the vehicle speed between two automatic speed cameras within the framework of traffic violation detection demonstrates that using the average speed metric enhances speed limit compliance accuracy. This method reduces the possibility of evading responsibility for violations through temporary speed reduction before cameras. These systems employ usage of existing road cameras infrastructure to determine the minimal travel path of vehicle passing two cameras placed at a certain distance apart to measure the average speed of travel. Technical aspects of implementing the proposed system include utilizing cloud computing for data processing and storage, which reduces infrastructure costs. The system employs the possibility of usage of machine learning algorithms to predict travel time between cameras, considering various factors such as road conditions and speed limits. This approach ensures high calculation accuracy and reduces the number of false violation alerts. To further reduce the possibility of false violations, it is suggested to only use speed limitations based on the traffic signs on the road intervals of the calculated minimal path between two cameras that the vehicle has passed. Implementing the system requires the development of new software for data analysis and integration with existing traffic control systems. This includes designing algorithms to determine the minimum required travel time between cameras and calculating the average speed based on these data. Additionally, methods must be developed to detect and handle exceptions, such as road stops, or route changes, which can affect calculation accuracy. The feasibility of practical implementation of the system was investigated based on the existing infrastructure of traffic cameras in the city of Lviv. Possible minimal routes between cameras were analyzed and compared to the avarage passing speed of vehicles of different categories. The modulated results indicate that such a system would be an effective addition to the traffic control system, while requiring relatively low financial and engineering efforts.

Authors

Publication Details

Journal
Information and communication technologies electronic engineering
Published
2024-09-01
DOI
https://doi.org/10.23939/ictee2024.02.093
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

EFFECTIVENESS ENHANCEMENT OF TRAFFIC CAMERAS BASED ON VEHICLES' AVERAGE SPEED CALCULATION

Oksana Urikova, Dmytro Chornyi, K. Morhoiev
Information and communication technologies electronic engineering
Autonomous Vehicle Technology and Safety
article

EFFECTIVENESS ENHANCEMENT OF TRAFFIC CAMERAS BASED ON VEHICLES' AVERAGE SPEED CALCULATION

Oksana Urikova, Dmytro Chornyi, K. Morhoiev
article en

Abstract

The analysis of calculating the vehicle speed between two automatic speed cameras within the framework of traffic violation detection demonstrates that using the average speed metric enhances speed limit compliance accuracy. This method reduces the possibility of evading responsibility for violations through temporary speed reduction before cameras. These systems employ usage of existing road cameras infrastructure to determine the minimal travel path of vehicle passing two cameras placed at a certain distance apart to measure the average speed of travel. Technical aspects of implementing the proposed system include utilizing cloud computing for data processing and storage, which reduces infrastructure costs. The system employs the possibility of usage of machine learning algorithms to predict travel time between cameras, considering various factors such as road conditions and speed limits. This approach ensures high calculation accuracy and reduces the number of false violation alerts. To further reduce the possibility of false violations, it is suggested to only use speed limitations based on the traffic signs on the road intervals of the calculated minimal path between two cameras that the vehicle has passed. Implementing the system requires the development of new software for data analysis and integration with existing traffic control systems. This includes designing algorithms to determine the minimum required travel time between cameras and calculating the average speed based on these data. Additionally, methods must be developed to detect and handle exceptions, such as road stops, or route changes, which can affect calculation accuracy. The feasibility of practical implementation of the system was investigated based on the existing infrastructure of traffic cameras in the city of Lviv. Possible minimal routes between cameras were analyzed and compared to the avarage passing speed of vehicles of different categories. The modulated results indicate that such a system would be an effective addition to the traffic control system, while requiring relatively low financial and engineering efforts.

Information and communication technologies electronic engineeringVol. 4(2)
Openalex Percentile: Top 84%
Autonomous Vehicle Technology and Safety
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EFFECTIVENESS ENHANCEMENT OF TRAFFIC CAMERAS BASED ON VEHICLES' AVERAGE SPEED CALCULATION — Oksana Urikova, Dmytro Chornyi, et al. · Information and communication technologies electronic engineering (2024) | TGRS Research Map | TGRS