Abstract
In recent years, with the rapid development of economy, more and more urban residents, while owning their own motor vehicles, are also troubled by the traffic congestion caused by the backward traffic facilities or traffic management methods. The loss of productivity, car accidents, high emissions, and environmental pollution caused by traffic congestion has become a huge and increasingly heavy burden on all countries in the world. Therefore, the prediction of urban road network traffic flow and the rapid and accurate evaluation of traffic congestion are of great significance to the study of urban traffic solutions. This paper focuses on how to apply data science technologies on vehicular networks data to present a prediction method for traffic congestion based on both real-time and predicted traffic data. Two evaluation frameworks are established, and existing methods are used to compare and evaluate the accuracy and efficiency of the presented method.
Highlights
The problem of urban traffic congestion, from the beginning of the birth of motor vehicles to the widespread popularity of motor vehicles, has been an important issue that puzzles countries all over the world [1]
In view of the existing standards and algorithms mentioned above, the evaluation algorithm described in this paper aims to be able to calculate and evaluate traffic congestion levels based on microscopic traffic flow characteristics
The first framework focuses on the crosswise comparison between the congestion evaluation algorithms described in this paper and several different algorithms under the same road conditions
Summary
The problem of urban traffic congestion, from the beginning of the birth of motor vehicles to the widespread popularity of motor vehicles, has been an important issue that puzzles countries all over the world [1]. A traffic economic theory analysis considers that the upgrading of basic transportation facilities is an efficient way to solve congestion. This problem cannot be completely solved by building better roads and facilities [2,3,4]. Road traffic flows consist of vehicles and their corresponding drivers, each of which has its own characteristics. A traffic flow is microscopic when it is considered to consist of a flow of a particular vehicle. It is still the usual practice to consider only the characteristics of traffic flow related to vehicles
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