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

Author:

MOSCOVICI Anca-Maria,SÎRBU Ovidiu Marcel,VÎLCEANU Clara-Beatrice,HERBAN SorinORCID,IOVANOVICI Alexandru

Abstract

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.

Publisher

Society of Land Measurements and Cadastre from Transylvania

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Supervised learning data preprocessing for short-term traffic flow prediction;2022 IEEE 16th International Scientific Conference on Informatics (Informatics);2022-11-23

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