Method for Identifying the Traffic Congestion Situation of the Main Road in Cold-Climate Cities Based on the Clustering Analysis Algorithm

Yulong Pei,Xiaoxi Cai,Keke Song,Jie Li,Rui Liu

doi:10.3390/su13179741

Abstract

Congestion has become a common urban disease in countries worldwide, with the acceleration of urbanization. The connotation of the congestion situation is expanded to describe, in detail, the traffic operation status and change characteristics of the main road in cold-climate cities and to provide more comprehensive identification methods and theoretical basis for cold-climate cities. It includes two aspects: the state and trend. A method to distinguish the traffic congestion state level and trend type of the main road in cold-climate cities is proposed on the basis of density clustering, hierarchical clustering, and fuzzy C-means clustering, and the temporal and spatial congestion characteristics of the main roads of cold-climate cities are explored. Research results show that we can divide the traffic congestion state into three levels: unblocked, slow, and congested. We can also divide the congestion trend into three types: aggravation, relief, and stability. This method is suitable for the identification of the main road’s congestion situation in cold-climate cities and can satisfy the spatiotemporal self-correlation and difference test. The temporal and spatial distribution rules of congestion are different under different road conditions, the volatility of the congestion degree and change speed on snowy and icy pavements, and the instability of congestion spatial aggregation are more serious than that on non-snowy and non-icy pavements. The research results are more comprehensive and objective than the existing methods.

Highlights

With rapid economic development and the accelerating urbanization process, the traffic demands of countries around the world have increased sharply
Identification Method of Traffic Congestion Trend of the Main Road in Considering the quantification of traffic congestion trends is the prerequisite for analyzing congestion evolution trends, this paper proposes congestion change speed indicators as the basis for judging the types of congestion evolution trends, that is, the ratio of the difference between the congestion state and the previous congestion state and the congestion duration, as shown in Equation (1)
In order to comprehensively and accurately analyze the congestion characteristics of cold-climate cities under severe climatic conditions, grasp the time and spatial distribution of congestion, and provide a basis for the treatment of traffic problems in coldclimate cities, the corresponding cluster analysis algorithm is selected to put forward a traffic congestion situation identification method suitable for the use of the urban main road in cold-climate cities to realize the transition from qualitative analysis to quantitative analysis in the traffic operation level of cold-climate cities, considering the advantages and disadvantages of different cluster analysis algorithms and applicable conditions

Summary

Introduction

With rapid economic development and the accelerating urbanization process, the traffic demands of countries around the world have increased sharply. Traffic congestion brings inconvenience to travel and life and causes additional fuel consumption, exhaust emissions, and noise pollution, as well as serious economic losses. According to the latest data released by the traffic information analysis company INRIX, the cost of traffic congestion was approximately $87 billion in the United States in 2018 [1]. The data updated by the European Commission on August 2020 show that traffic congestion in European Union countries causes economic losses of nearly 100 billion euros every year, accounting for approximately 1% of Gross Domestic Product (GDP).

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