مهندسی عمران-راه و ترابری
Ahamad Jawad Ramaki; Reza Amin; Ali Khodaii
Abstract
Recognizing traffic signs is very important in the field of intelligent transportation systems, because it effectively increases the safety of our roads. By equipping drivers with vital information about potential hazards, this technology significantly reduces response time and helps making quick decisions ...
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Recognizing traffic signs is very important in the field of intelligent transportation systems, because it effectively increases the safety of our roads. By equipping drivers with vital information about potential hazards, this technology significantly reduces response time and helps making quick decisions while operating the vehicle. Due to the exponential growth of our population, unfortunately the increase in the number of vehicles has led to a painful increase in traffic fatalities and injuries. Although the expansion of the transportation network helps the traffic issue, this expansion may be inapplicable due to the High financial costs, geographic and environmental limitations, as well as a long period of time to improve transportation infrastructure. Quality control of traffic colors, shabrangs, glass beads and other traffic signs in accordance with national and international standards will significantly reduce the number of dead and injured. Managing a smart city with emphasis on waste reduction and efficient use of resources is the main responsibility of traffic and transportation activities. The use of complex processing techniques in cars to increase safety without interfering with driving has been proposed as part of the concept of a smart city. This study looks at a new approach that can help create a framework for placing street signs using Google images into a traffic management program. The findings show a reduction in travel time, an increase in the use of the fleet, better maintenance of vehicles, and a reduction in carbon dioxide emissions from passenger cars.
mohsen amouzadeh omrani; pouyan nazarian
Volume 2, Issue 9 , December 2021, , Pages 57-73
Abstract
Traffic sign recognition plays a vital role in the intelligent transportation system, which increases traffic safety by providing safety and precautionary information about road hazards to drivers. Knowledge of how humans process the meaning of symptoms reduces the time it takes to respond to them and ...
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Traffic sign recognition plays a vital role in the intelligent transportation system, which increases traffic safety by providing safety and precautionary information about road hazards to drivers. Knowledge of how humans process the meaning of symptoms reduces the time it takes to respond to them and make decisions while driving. Although the expansion of the transportation network helps in the discussion of traffic, this expansion may not be feasible due to high financial costs, geographical and environmental constraints, as well as long-term improvements to transportation infrastructure. These limitations can be minimized with Traffic Management Systems (TMS). Efficient use of resources and waste reduction are key goals in managing a smart city, in which traffic and transportation activities have a significant impact. In smart city approaches, the use of intelligent processing methods in vehicles to increase safety is proposed without any interference in the driving process. This study addresses an innovative system that aims to assist councils in developing a road management plan and creating a framework for placing street signs and intelligent car systems using Google Images (GSV). Recent advances in machine memory detection technology have provided Google Automated Images with an automated approach to identifying and classifying street signs, allowing it to be used to produce a standalone image recognition system to improve traffic information monitoring and storage. This article reviews and compares studies and developments related to traffic signs and signs in smart cities and intelligent transportation systems. The results show a reduction in travel time, improved vehicle maintenance and transportation system logistics, better fleet utilization, reduced vehicle fuel consumption and CO2 emissions.
