Evaluation of Traffic Crossings Situations using Machine Learning

Hlavacek, Jakub; Gotthans, Jakub

doi:10.1109/radioelektronika54537.2022.9764937

Cited by 2 publications

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“…Fuzzy Implication is a group of rules and conditional statements. For example, if the temperature is medium and humidity is low the weather is good [21], [22].…”

Section: Logical Operations Using Fuzzy Logicmentioning

confidence: 99%

A Controlling Traffic Light system using Fuzzy logic

Gdeeb

2023

JQCM

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Automatic control systems are a new advanced system uses computers and hardware controllers to act as a driving system. Increasing in cars numbers while we have the same infrastructure caused a large traffic problem so we need automatic adaptive controllers to control the open and close tasks of traffic light system. Fuzzy Logic is a conversation from classical logic with values of 0 for false and 1 for true to a range of values between 0 and 1. This study aims to create an adaptive traffic control system using fuzzy logic and image processing, we have a camera on each traffic light to calculate the number of cars there and then we feed the number of cars to a fuzzy logic system to decide which traffic light must become on

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“…Fuzzy Implication is a group of rules and conditional statements. For example, if the temperature is medium and humidity is low the weather is good [21], [22].…”

Section: Logical Operations Using Fuzzy Logicmentioning

confidence: 99%

A Controlling Traffic Light system using Fuzzy logic

Gdeeb

2023

JQCM

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“…The IR Agarwal and Rai (2022) sensors arranged at four lanes to detect presence of the vehicles and rain sensor Yang et al (2022) to presence the rain condition. The sensors data is given to ARDUINO MEGA Hlavacek and Gotthans (2022) which processes data to control traffic signals accordingly to road status based on fuzzy logic control. Seven segments display-based count timer are used.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Logic-Based Smart Traffic Management Systems

Abdou¹,

Farrag²,

Tolba³

2022

Journal of Computer Science

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Traffic congestion is a serious problem in many developing countries like Egypt. In the presence of the traditional traffic light system, it creates health risks, wastes time and fuel, and pollutes the air. Therefore, there is a big need for a smart traffic management system. This study contributes in solving this problem by introducing an artificial intelligence-based smart traffic light system using fuzzy logic to ensure the smooth flow of traffic in cities. Research results indicate that smart traffic light management is very crucial in smart cities to reduce their carbon footprint to save the world and save energy. Other possible application could be implemented with minor system upgrades such as Detection and Management of traffic Congestion, Automatic Billing of Toll Charges, Automatic detection of speed limit Violation, Route planning, Intelligent Internet of Vehicles, and Prevention of Road Accidents. Four traffic light approaches (fixed-time, smart-time, fixedtime-fuzzy logic, and smart-time-fuzzy-logic) are developed with different eight traffic scenarios. The four approaches are applied with two tools, the first tool is a real Marquette which consists of 4 roads with only one or two vehicles. The second is a simulation software which consists of 4 roads with more than 100 vehicles through 10 min. Many sensors such as (IR sensors, rain sensors, and LEDs to control traffic light) are used to collect data and then the fuzzy algorithm is used to ensure the smooth flow of traffic in cities. The traffic data acquired from the vehicles is fed into the proposed model to maximize the duration of the green light based on the road state. According to experimental results, the proposed smart fuzzy technique simulation software reduced the average waiting time of the vehicles from 769 to 289 sec in heavy rain condition. It also reduced the total time for all vehicles from 2490 to 1154 sec.

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Evaluation of Traffic Crossings Situations using Machine Learning

Cited by 2 publications

References 0 publications

A Controlling Traffic Light system using Fuzzy logic

A Controlling Traffic Light system using Fuzzy logic

A Fuzzy Logic-Based Smart Traffic Management Systems

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