scholarly journals Traffic Light Signal Parameters Optimization using Modification of Multielement Genetic Algorithm

2018 ◽  
Vol 8 (1) ◽  
pp. 246 ◽  
Author(s):  
I Gede Pasek Suta Wijaya ◽  
Keeichi Uchimura ◽  
Gou Koutaki
Keyword(s):  
Genetic Algorithm ◽  
Traffic Congestion ◽  
Road Network ◽  
Hash Table ◽  
Optimization Methods ◽  
Light Signal ◽  
Parameters Optimization ◽  
Traffic Light ◽  
Swarm Optimization ◽  
Signal Parameters

A strategy to optimize traffic light signal parameters is presented for solving traffic congestion problem using modification of the Multielement Genetic Algorithm (MEGA). The aim of this method is to improve the lack of vehicle throughput (FF ) of the works called as traffic light signal parameters optimization using the MEGA and Particle Swarm Optimization (PSO). In this case, the modification of MEGA is done by adding Hash-Table for saving some best populations for accelerating the recombination process of MEGA which is shortly called as H-MEGA. The experimental results show that the H-MEGA based optimization provides better performance than MEGA and PSO based methods (improving the FF of both MEGA and PSO based optimization methods by about 10.01% (from 82,63% to 92.64%) and 6.88% (from 85.76% to 92.64%), respectively). In addition, the H-MEGA improve significantly the real FF of Ooe Toroku road network of Kumamoto City, Japan about 21.62%.

scholarly journals Automatic traffic light controller for emergency vehicle using peripheral interface controller

2019 ◽  
Vol 9 (3) ◽  
pp. 1788 ◽  
Author(s):  
Norlezah Hashim ◽  
Fakrulradzi Idris ◽  
Ahmad Fauzan Kadmin ◽  
Siti Suhaila Jaapar Sidek
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Emergency Situation ◽  
Light Signal ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Light Area ◽  
On The Road

Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.

scholarly journals A COMPARISON OF SIMULATED ANNEALING, GENETIC ALGORITHM AND PARTICLE SWARM OPTIMIZATION IN OPTIMAL FIRST-ORDER DESIGN OF INDOOR TLS NETWORKS

2017 ◽  
Vol IV-2/W4 ◽  
pp. 75-82 ◽  
Author(s):  
F. Jia ◽  
D. Lichti
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Simulated Annealing ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Network Design Problem ◽  
Design System ◽  
Swarm Optimization ◽  
First Order

The optimal network design problem has been well addressed in geodesy and photogrammetry but has not received the same attention for terrestrial laser scanner (TLS) networks. The goal of this research is to develop a complete design system that can automatically provide an optimal plan for high-accuracy, large-volume scanning networks. The aim in this paper is to use three heuristic optimization methods, simulated annealing (SA), genetic algorithm (GA) and particle swarm optimization (PSO), to solve the first-order design (FOD) problem for a small-volume indoor network and make a comparison of their performances. The room is simplified as discretized wall segments and possible viewpoints. Each possible viewpoint is evaluated with a score table representing the wall segments visible from each viewpoint based on scanning geometry constraints. The goal is to find a minimum number of viewpoints that can obtain complete coverage of all wall segments with a minimal sum of incidence angles. The different methods have been implemented and compared in terms of the quality of the solutions, runtime and repeatability. The experiment environment was simulated from a room located on University of Calgary campus where multiple scans are required due to occlusions from interior walls. The results obtained in this research show that PSO and GA provide similar solutions while SA doesn’t guarantee an optimal solution within limited iterations. Overall, GA is considered as the best choice for this problem based on its capability of providing an optimal solution and fewer parameters to tune.

Smart Cities: Study and Comparison of Traffic Light Optimization in Modern Urban Areas Using Artificial Intelligence

2018 ◽  
Vol 8 (2) ◽  
pp. 10
Author(s):  
Mustapha Kabrane ◽  
Salah-ddine Krit ◽  
Lahoucine El Maimouni
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Road Network ◽  
Smart Cities ◽  
Optimization Techniques ◽  
Traffic Light ◽  
Large Cities ◽  
Traffic Lights ◽  
The Road ◽  
Road Signs

In large cities, the increasing number of vehicles private, society, merchandise, and public transport, has led to traffic congestion. Users spend much of their time in endless traffic congestion. To solve this problem, several solutions can be envisaged. The interest is focused on the  system of road signs: The use of a road infrastructure is controlled by a traffic light controller, so it is a matter of knowing how to make the best use of the controls of this system (traffic lights) so as to make traffic more fluid. The values of the commands computed by the controller are determined by an algorithm which is ultimately, only solves a mathematical model representing the problem to be solved. The objective is to make a study and then the comparison on the optimization techniques based on artificial intelligence1 to intelligently route vehicle traffic. These techniques make it possible to minimize a certain function expressing the congestion of the road network. It can be a function, the length of the queue at intersections, the average waiting time, also the total number of vehicles waiting at the intersection

scholarly journals Smart Traffic Lights over Vehicular Named Data Networking

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 83 ◽  
Author(s):  
Majed Al-qutwani ◽  
Xingwei Wang
Keyword(s):  
Traffic Congestion ◽  
Fixed Time ◽  
Light Signal ◽  
Vehicular Traffic ◽  
Named Data Networking ◽  
Traffic Light ◽  
Traffic Lights ◽  
Light System ◽  
Smart Traffic ◽  
Data Networking

The existing traffic light system fails to deal with the increase in vehicular traffic requirements due to fixed time programming. Traffic flow suffers from vehicle delay and congestion. A new networking technology called vehicular ad hoc networking (VANET) offers a novel solution for vehicular traffic management. Nowadays, vehicles communicate with each other (V2V), infrastructure (V2I), or roadside units (V2R) using IP-based networks. Nevertheless, IP-based networks demonstrate low performance with moving nodes as they depend on communication with static nodes. Currently, the research community is studying a new networking architecture based on content name called named data networking (NDN) to implement it in VANET. NDN is suitable for VANET as it sends/receives information based on content name, not content address. In this paper, we present one of VANET’s network applications over NDN, a smart traffic light system. Our system solves the traffic congestion issue as well as reducing the waiting time of vehicles in road intersections. This system replaces the current conventional system with virtual traffic lights (VTLs). Instead of installing traffic lights at every intersection, we utilize a road side unit (RSU) to act as the intersection controller. Instead of a light signal, the RSU collects the orders of vehicles that have arrived or will arrive at the intersection. After processing the orders according to the priority policy, the RSU sends an instant message for every vehicle to pass the intersection or wait for a while. The proposed system mimics a human policeman intersection controlling. This approach is suitable for autonomous vehicles as they only receive signals from the RSU instead of processing many images. We provide a map of future work directions for enhancing this solution to take into account pedestrian and parking issues.

scholarly journals DETERMINATION OF THE CONDITIONS FOR THE APPLICATION OF THE F. WEBSTER FORMULA FOR DETERMINING THE TRANSPORT DELAY AT A CIRCULAR INTERSECTION WITH TRAFFIC LIGHT REGULATION AND A CUT-THROUGH CENTRAL ISLAND

2021 ◽  
pp. 76-86
Author(s):  
Yu.Ya. Komarov ◽  
◽  
S.V. Ganzin ◽  
D.D. Silchenkov ◽  
◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Road Traffic ◽  
High Reliability ◽  
Calculated Data ◽  
Light Regulation ◽  
Traffic Light ◽  
Software Complex ◽  
Transport Delay ◽  
The Road

The main method of determining transport delay in the national methodical and educational literature is its calculation according to the methodology (formula) of F. Webster (1958), which is based on the theory of mass service. However, in conditions of high traffic congestion or traffic congestion, experimental and calculated data at simple intersections vary considerably. The definition of delays for complex intersections, in particular for the Hamburger Through-About Intersection (further HTAI) is also contradictory. The aim of the study is to improve determine the area of application of F. Webster’s formula for a little-studied roundabouts HTAI. For the first time, the paper addresses the selection of parameters of the HTAI in urban settings, and also introduces a method of calculating transport delays depending on various factors. For the purpose of the study, the hypothesis is put forward that the application of the Webster formula depends on the intensity of traffic on the main and secondary roads, the degree of loading in directions and transport demand for left-turning traffic. According to the hypothesis, on the basis of the collected data, transport delays are calculated on the HTAI from the selected factors. To justify the adequacy of calculations, the method of simulation in the Aimsun (micro-modeling) software complex is used. On the basis of in-kind surveys of section of the road network, a high-reliability simulation model was created, reflecting the current situation at regulated intersection, and also assessed the feasibility of using the HTAI on a section of the road network. There are dependencies of transport delays on traffic in the main and secondary road, effective duration of the cycle of regulation on the main road, traffic on roundabout, the diameter of the islet for the HTAI. Thus, based on the resulting mathematical model, the range of application of the Webster formula is defined, which is affected by the number of lanes for the main and secondary roads, the degree of loading in directions and the number of lanes on the ring. Further research involves the development of a methodology for calculating the parameters of the HTAI.

scholarly journals A comparative study of PSO, GSA and SCA in parameters optimization of surface grinding process

2019 ◽  
Vol 8 (3) ◽  
pp. 1117-1127
Author(s):  
Teh Muy Shin ◽  
Asrul Adam ◽  
Amar Faiz Zainal Abidin
Keyword(s):  
Optimization Methods ◽  
Pso Algorithm ◽  
Parameters Optimization ◽  
Surface Grinding ◽  
Grinding Process ◽  
Swarm Optimization ◽  
Optimum Parameters ◽  
Maximum Production Rate ◽  
The Cost ◽  
Selection Of

The selection of parameters in grinding process remains as a crucial role to guarantee that the machined product quality is at the minimum production cost and maximum production rate. Therefore, it is required to utilize more advance and effective optimization methods to obtain the optimum parameters and resulting an improvement on the grinding performance. In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. The efficiency of the three algorithms are evaluated and comparedwith previous results obtained by other optimization methods on similar studies.The experimental results showed that PSO algorithm achieves better optimization performance in the aspect of convergence rate and accuracy of best solution.Whereas in the comparison of results of previous researchers, the obtained result of PSO proves that it is efficient in solving the complicated mathematical model of surface grinding process with different conditions.

Optimization Methods for Estimation of Missing Data

2010 ◽  
pp. 210-232
Author(s):  
Tshilidzi Marwala
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Simulated Annealing ◽  
Missing Data ◽  
Missing Values ◽  
Particle Swarm ◽  
Optimization Methods ◽  
Hill Climbing ◽  
Swarm Optimization ◽  
Design Variables

This chapter presents various optimization methods to optimize the missing data error equation, which is made out of the autoassociative neural networks with missing values as design variables. The four optimization techniques that are used are: genetic algorithm, particle swarm optimization, hill climbing and simulated annealing. These optimization methods are tested on two datasets, namely, the beer taster dataset and the fault identification dataset. The results that are obtained are then compared. For these datasets, the results indicate that genetic algorithm approach produced the highest accuracy when compared to simulated annealing and particle swarm optimization. However, the results of these four optimization methods are the same order of magnitude while hill climbing produces the lowest accuracy.

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