Traffic Congestion Index Evaluation Based on Travel Speed on Urban Expressway

ICTE 2013 ◽  
2013 ◽  
Author(s):  
Xiaofang Shan ◽  
Zheng Wang ◽  
Qiang Liu
2018 ◽  
Vol 10 (6) ◽  
pp. 168781401878148 ◽  
Author(s):  
Wan-Xiang Wang ◽  
Rui-Jun Guo ◽  
Jing Yu

Traffic congestion index reflects the state of traffic flow. The detection and analysis on traffic congestion index can be used to estimate the operation status of roads, to plan and organize road traffic for traffic managers, and to make the reasonable decisions of travelers to travel. The traffic conditions of several evaluation indexes were analyzed. Based on the theory of fuzzy mathematics, some membership functions of the evaluating indexes were designed. Three calculation methods of traffic congestion index were proposed. Their calculation results were compared mutually. The conclusion revealed that using saturation calculated by the corresponding service level of traffic congestion index not well reflect the traffic situation, what’s more, travel speed is used to calculate the congestion index of the first method. Using comprehensive parameters can calculate the congestion index of the third method. Both them are roughly similar and in line with the actual traffic phenomenon.


Author(s):  
Yi Li ◽  
Weifeng Li ◽  
Qing Yu ◽  
Han Yang

Urban traffic congestion is one of the urban diseases that needs to be solved urgently. Research has already found that a few road segments can significantly influence the overall operation of the road network. Traditional congestion mitigation strategies mainly focus on the topological structure and the transport performance of each single key road segment. However, the propagation characteristics of congestion indicate that the interaction between road segments and the correlation between travel speed and traffic volume should also be considered. The definition is proposed for “key road cluster” as a group of road segments with strong correlation and spatial compactness. A methodology is proposed to identify key road clusters in the network and understand the operating characteristics of key road clusters. Considering the correlation between travel speed and traffic volume, a unidirectional-weighted correlation network is constructed. The community detection algorithm is applied to partition road segments into key road clusters. Three indexes are used to evaluate and describe the characteristic of these road clusters, including sensitivity, importance, and IS. A case study is carried out using taxi GPS data of Shanghai, China, from May 1 to 17, 2019. A total of 44 key road clusters are identified in the road network. According to their spatial distribution patterns, these key road clusters can be classified into three types—along with network skeletons, around transportation hubs, and near bridges. The methodology unveils the mechanism of congestion formation and propagation, which can offer significant support for traffic management.


2015 ◽  
Vol 30 (30) ◽  
pp. 123-134 ◽  
Author(s):  
Nilanchal Patel ◽  
Alok Bhushan Mukherjee

Abstract Traffic congestion is a major and growing problem in urban areas across the globe. It reduces the effective spatial interaction between different locations. To mitigate traffic congestion, not only the actual status of different routes needs to be known but also it is imperative to determine network congestion in different spatial zones associated with distinct land use classes. In the present paper, a new formula is proposed to quantify traffic congestion in the different spatial zones of a study area characterized by distinct land use classes. The proposed formula is termed the Traffic Congestability Value (TCV). The formula considers three major influencing factors: congestion index value, pedestrian movement and road surface conditions; since these parameters are significantly related to land use in a region. The different traffic congestion parameters, i.e. travel time, average speed and the proportion of time stopped, were collected in real time. Lower values of TCV correspond to a higher degree of congestion in the respective spatial zones and vice-versa and the results were validated in the field. TCV differs from the previous approaches to quantifying traffic congestion since it focuses on the causes of network congestion while in previous works the focus was generally on link flow congestion.


2014 ◽  
Vol 1030-1032 ◽  
pp. 2182-2186
Author(s):  
Ling Yan Ge ◽  
Bi Feng Zhu

With the rapid development of urbanization in China and the motorization’s fast pace of high speed as well as the national automobile industry process, many cities in our country have been facing a huge problem - traffic congestion in recent years. And the essence of the problem is the imbalance between road traffic supply and traffic demand in the process of urban development. Aimed at the problem of traffic congestion, this paper based on Hangzhou city’s traffic congestion index of monitoring data from testing platform and statistical data from field survey , studied the Hangzhou east area of road traffic running situation, analyzed the causes of the east area of Hangzhou road congestion, and thus to adjust and optimize the road traffic system of the area, put forward reasonable system solutions and proposals to improve the management level


2013 ◽  
Vol 409-410 ◽  
pp. 1209-1212
Author(s):  
Da Shan Chen

The macroscopic traffic flow parameters characteristic is an important research content in traffic flow theory. Urban expressway plays an important role in the urban road network. It is gradually shifting from large-scale infrastructure-oriented to refinement of traffic management. With the growing of traffic demand and much more traffic congestion and accidents, integrated active traffic management should be involved in urban expressway management on the back ground of car-road coordination. As the backbone road network, traffic flow characteristic parameters have great value for the control and management of urban expressway. Then the characteristic variables of the expressway traffic flow were identified which support meticulous management for urban expressway.


2013 ◽  
Vol 409-410 ◽  
pp. 1339-1342 ◽  
Author(s):  
He Mao ◽  
Xiu Hua Xu

According to the urban expressway traffic congestion of Beijing, from the perspective of traffic flow, the study makes a calculation and analysis on road network congestion rate, load of road network and traffic operation index. Training the traffic congestion and load of road network by using the BP neutral network in MATLAB, and put forward some countermeasures to solve the problem of traffic congestion. Through analyzing the load of different section and congestion rate, we can obtain the spatial distribution of the traffic flow and grasp the overall traffic on the Ring Road running load, develop appropriate management control programs for traffic managers, provide service and travel mode for travelers at the same time, so that balance the overall network load tends.


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