Traffic micro-simulation as a validation tool for developing genetic algorithms for green wave optimization

Iovanovici, Alexandru; Avramoni, Dacian; Moscovici, Anca-Maria; Prodan, Lucian

doi:10.1109/saci49304.2020.9118841

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…The study aims to present the workflow that includes identifying the elements of a traffic light intersection, measuring and processing them, in order to realize a layout plan that can be introduced into a GIS system to manage traffic lights in an intelligent manner (Iovanovici et al, 2020). It has an interdisciplinary character as it includes knowledge from different disciplines such as GIS, topography and road engineering and it highlights the importance of permanently updating the urban GIS for an efficient urban planning with a view to offering high living standards for the city's inhabitants.…”

Section: Introduction Introduction Introduction Introductionmentioning

confidence: 99%

Spatial data acquisition for traffic lights intersections as a basis for GIS development in Timisoara, Romania

et al. 2022

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The continuous development and the rapid economic growth of Timisoara municipality (western Romania) have contributed to the increase in transport needs. The number of motor vehicles registered by natural persons (125195), and the number of motor vehicles registered by legal entities (35303), results in one motor vehicle per two persons. To these figures are added the commuters, students and tourists who come by car to the city. Thus, the main cause of road traffic is the increasing number of vehicles, day by day. In order to maximize road capacity and speed up the pedestrians’ flow, traffic lights are used at approximately every intersection. As such, the proper use of traffic signals can lead to more efficient traffic management. Due to the evolution in time, technology comes to aid precisely to solve such problems and especially to streamline road traffic issues. Thus, the article presents the workflow that includes identifying the elements of a traffic light intersection, measuring, and processing them, in order to realize a layout plan that can be introduced into a GIS system to manage traffic lights in an intelligent manner. Using GIS (Geographical Information System) technology, the problem of road traffic can be solved appropriately and efficiently. Based on the main characteristics of urban traffic and the efficient, appropriate use of traffic lights, approaching, and treating the information according to the area, its spatial and geographical location through coordinates, GIS technology can be used to solve problems given by the zonal agglomeration of heavy traffic centres, or areas with peak hours. The fluidization of the traffic can ensure better circulation and aeration of the crowded areas and the avoidance of the congestion of some central arteries, especially during rush hours.

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Section: Introduction Introduction Introduction Introductionmentioning

confidence: 99%

Spatial data acquisition for traffic lights intersections as a basis for GIS development in Timisoara, Romania

et al. 2022

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Road Intersection Optimization with Resource-Constrained Metaheuristic: A Case Study

Szatmari

Prodan

Iovanovici

et al. 2022

2022 IEEE 20th Jubilee International Symposium on Intelligent Systems and Informatics (SISY)

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Travel time reliability prediction by genetic algorithm and machine learning models

Zargari

Khorshidi

Mirzahossein

et al. 2024

Proceedings of the Institution of Civil Engineers - Transport

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Travel time reliability has proved to be a critical issue both in the context of traveller's choices and decisions and freight transportation. In the terminology, the temporal variability of travel time is known as reliability and is affected by numerous factors. Three of them, including traffic volume, incidents, and inclement weather, are among the most profound, and their effects have been the subject of many studies. What has made this article unique is the simultaneous implementation of a genetic algorithm with multiple machine learning methods. Also, GA could eliminate overfitting, which is a common mistake in ML models. The numerical results revealed that the performance of the prior model, KNN, enhanced significantly when GA was imposed on it. In terms of stability ratio, a 12% decrease was observed. Also, the mean squared error (MSE) for the training set and test set decreased. However, the reduction was not significant. To further illustrate the advantages of GA implementation, the number of predictions with MAPE greater than 0.05 were compared, and a notable reduction was revealed. In the final step, sensitivity analysis was done to depict how PTI responds to the fluctuations of independent variables.

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Traffic micro-simulation as a validation tool for developing genetic algorithms for green wave optimization

Cited by 3 publications

References 14 publications

Spatial data acquisition for traffic lights intersections as a basis for GIS development in Timisoara, Romania

Spatial data acquisition for traffic lights intersections as a basis for GIS development in Timisoara, Romania

Road Intersection Optimization with Resource-Constrained Metaheuristic: A Case Study

Travel time reliability prediction by genetic algorithm and machine learning models

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