Road Traffic Control Based on Genetic Algorithm for Reducing Traffic Congestion

2011 ◽  
Vol 131 (6) ◽  
pp. 1190-1198 ◽  
Author(s):  
Yuji Shigehiro ◽  
Takuya Miyakawa ◽  
Tatsuya Masuda
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Road Traffic

Road traffic control based on genetic algorithm for reducing traffic congestion

2012 ◽  
Vol 95 (4) ◽  
pp. 11-19 ◽  
Author(s):  
Yuji Shigehiro ◽  
Takuya Miyakawa ◽  
Tatsuya Masuda
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Road Traffic

scholarly journals INTELLIGENT TRAFFIC CONTROL DEVICE MODEL USING AD HOC NETWORK

2019 ◽  
Vol 01 (02) ◽  
pp. 68-76
Author(s):  
Robert Bestak
Keyword(s):  
Traffic Flow ◽  
Automobile Industry ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Communication Systems ◽  
Ad Hoc ◽  
Road Traffic ◽  
Control Device ◽  
Device Model

The advancements in the technologies related to the wireless communication systems has made the vehicular adhoc networks prominent area of research in the automobile industry. The absolute volume of road traffic affects the safety, convenience and the efficiency of the traffic flow in the urban areas. So the paper scopes in developing an intelligent traffic control device model using the adhoc network to ameliorate the traffic flow. The proposed system enhances the convenience in travel by gathering the information of the vehicles along with the density of the vehicles and the movement of the vehicles on road. The device is modelled using the MATLAB and examined over the traffic flow on the peak hours as well as the normal hours and the holidays to understand its intelligent traffic control. The results obtained shows that the performance improvement in optimizing the traffic congestion through the proposed method is better compared to the existing methodologies used in traffic controlling.

scholarly journals Multirunway Optimization Schedule of Airport Based on Improved Genetic Algorithm by Dynamical Time Window

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Hang Zhou ◽  
Xinxin Jiang
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Time Window ◽  
Air Traffic ◽  
Operating Conditions ◽  
Improved Genetic Algorithm ◽  
Flight Delays ◽  
Effective Measure ◽  
Dynamical Time

Reasonable airport runway scheduling is an effective measure to alleviate air traffic congestion. This paper proposes a new model and algorithm for flight scheduling. Considering the factors such as operating conditions and flight safety interval, the runway throughput, flight delays cost, and controller workload composes a multiobjective optimization model. The genetic algorithm combined with sliding time window algorithm is used to solve the model proposed in this paper. Simulation results show that the algorithm presented in this paper gets the optimal results, the runway throughput is increased by 12.87%, the delay cost is reduced by 61.46%, and the controller workload is also significantly reduced compared with FCFS (first come first served). Meanwhile, compared with the general genetic algorithm, it also reduces the time complexity and improves real-time and work efficiency significantly. The analysis results can provide guidance for air traffic controllers to make better air traffic control.

Delay Optimization Using Genetic Algorithm at the Road Intersection

2019 ◽  
Vol 9 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Bharti Sharma ◽  
Sachin Kumar
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Road Traffic ◽  
Real Data ◽  
Traffic Data ◽  
Control Performance ◽  
Traffic Flows ◽  
The Road ◽  
Detection Systems ◽  
The City

Metropolitan road traffic mechanisms in developing countries are a critical problem due to fast motorization. The optimization of traffic control is one method to decrease this problem. In this study, a genetic algorithm was implemented to minimize delay at an intersection by finding red and green cycle intervals at an intersection. The objective function minimizes the delay at an intersection and increases progressive flows of traffic on roads. The study was done on real data collected from three t- intersections in the city of Hardwar, India. Traffic data for traffic flows, queue sizes, and traffic speed are collected using video detection systems in the study area. The digital images from the camera were analyzed in real time. The results show that the traffic control performance is improved up to 85% over existing algorithms proposed by the same author.

Smart Traffic System Operations

2019 ◽  
pp. 171-190
Author(s):  
Neelu Khare ◽  
Shruthy Bhavanasi
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Motion Sensors ◽  
Control Activity ◽  
Traffic System ◽  
The World ◽  
Smartphone Technology ◽  
Iot Devices ◽  
Smart Traffic

Traffic congestion is a growing problem in the world. It causes waste of time and fuel, increases pollution and stress. This is especially of road traffic in India, which faces problems like congestion, unpredictable travel time, urban chaos and noise. A smart traffic system automates the traffic control activity in order to obtain preference for the lanes on the basis of certain parameters. Hence, it provides an automatic control on the traffic in an optimized manner. It takes inputs from various sensors (utilising ultrasonic sensors, light sensors, motion sensors, cameras and IoT devices) and sends interrupt signals to the controlling devices. It consists of the IoT (Internet of Things) coupled with smartphone technology, RFID, sensors and a LADAR system. The system deals with the major issues of traffic congestion and collision avoidance and suggests remedies to tackle the same. In this chapter, various methodologies and architectures for smart traffic system operations are described.

Delay Optimization Using Genetic Algorithm at the Road Intersection

2021 ◽  
pp. 762-772
Author(s):  
Bharti Sharma ◽  
Sachin Kumar
Keyword(s):  
Genetic Algorithm ◽  
Developing Countries ◽  
Traffic Control ◽  
Road Traffic ◽  
Digital Images ◽  
Real Data ◽  
The Road ◽  
Detection Systems ◽  
Delay Optimization ◽  
The City

Metropolitan road traffic mechanisms in developing countries are a critical problem due to fast motorization. The optimization of traffic control is one method to decrease this problem. In this study, a genetic algorithm was implemented to minimize delay at an intersection by finding red and green cycle intervals at an intersection. The objective function minimizes the delay at an intersection and increases progressive flows of traffic on roads. The study was done on real data collected from three t- intersections in the city of Hardwar, India. Traffic data for traffic flows, queue sizes, and traffic speed are collected using video detection systems in the study area. The digital images from the camera were analyzed in real time. The results show that the traffic control performance is improved up to 85% over existing algorithms proposed by the same author.

scholarly journals Determining the Optimal Restricted Driving Zone Using Genetic Algorithm in a Smart City

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2276
Author(s):  
Tony Jan ◽  
Pegah Azami ◽  
Saeid Iranmanesh ◽  
Omid Ameri Sianaki ◽  
Shiva Hajiebrahimi
Keyword(s):  
Genetic Algorithm ◽  
Air Pollution ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Fitness Function ◽  
Traffic Load ◽  
Regression Problem ◽  
Restricted Area ◽  
Trade Off ◽  
Citizen Satisfaction

Traffic control is one of the most challenging issues in metropolitan cities with growing populations and increased travel demands. Poor traffic control can result in traffic congestion and air pollution that can lead to health issues such as respiratory problems, asthma, allergies, anxiety, and stress. The traffic congestion can also result in travel delays and potential obstruction of emergency services. One of the most well-known traffic control methods is to restrict and control the access of private vehicles in predetermined regions of the city. The aim is to control the traffic load in order to maximize the citizen satisfaction given limited resources. The selection of restricted traffic regions remains a challenge because a large restricted area can reduce traffic load but with reduced citizen satisfaction as their mobility will be limited. On the other hand, a small restricted area may improve citizen satisfaction but with a reduced impact on traffic congestion or air pollution. The optimization of the restricted zone is a dynamic multi-regression problem that may require an intelligent trade-off. This paper proposes Optimal Restricted Driving Zone (ORDZ) using the Genetic Algorithm to select appropriate restricted traffic zones that can optimally control the traffic congestion and air pollution that will result in improved citizen satisfaction. ORDZ uses an augmented genetic algorithm and determinant theory to randomly generate different foursquare zones. This fitness function considers a trade-off between traffic load and citizen satisfaction. Our simulation studies show that ORDZ outperforms the current well-known methods in terms of a combined metric that considers the least traffic load and the most enhanced citizen satisfaction with over 30.6% improvements to some of the comparable methods.

scholarly journals Review of traffic control techniques for emergency vehicles

2019 ◽  
Vol 13 (3) ◽  
pp. 1243
Author(s):  
Wan Mohd Hafiz bin Wan Hussin ◽  
Marshima Mohd Rosli ◽  
Rosmawati Nordin
Keyword(s):  
Control System ◽  
Radio Frequency Identification ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Control Technique ◽  
Emergency Vehicle ◽  
Control Techniques ◽  
Emergency Vehicles ◽  
Traffic Control System

<span>Traffic control system play an important role to manage traffic congestion on the road especially during peak hours and peak seasons. One of the main challenges is to control the traffic when there are emergency cases at traffic light intersection especially peak hours. This could affect the route for emergency vehicles such as ambulance, fire brigade and police car to reach their destination. Due to the increase of traffic congestion during peak hours and peak seasons in Malaysia, there is a need for further evaluation of traffic control techniques. This paper reviewed and consolidated information on the different types of the existing traffic control system for road traffic management such as Radio Frequency Identification (RFID), wireless sensor network and image processing. This paper analysed and compared on the design, benefits and limitations of each technique. Through the reviews, this paper recommends the best traffic control technique for emergency vehicle that offers low price, low maintenance and can be used in various areas of applications.</span>

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