scholarly journals Mining Topological Dependencies of Recurrent Congestion in Road Networks

2021 ◽  
Vol 10 (4) ◽  
pp. 248
Author(s):  
Nicolas Tempelmeier ◽  
Udo Feuerhake ◽  
Oskar Wage ◽  
Elena Demidova

The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including urban planning and the scheduling of public transportation services. While most existing studies investigate temporal patterns of RC phenomena, the influence of the road network topology on RC is often overlooked. This article proposes the ST-Discovery algorithm, a novel unsupervised spatio-temporal data mining algorithm that facilitates effective data-driven discovery of RC dependencies induced by the road network topology using real-world traffic data. We factor out regularly reoccurring traffic phenomena, such as rush hours, mainly induced by the daytime, by modelling and systematically exploiting temporal traffic load outliers. We present an algorithm that first constructs connected subgraphs of the road network based on the traffic speed outliers. Second, the algorithm identifies pairs of subgraphs that indicate spatio-temporal correlations in their traffic load behaviour to identify topological dependencies within the road network. Finally, we rank the identified subgraph pairs based on the dependency score determined by our algorithm. Our experimental results demonstrate that ST-Discovery can effectively reveal topological dependencies in urban road networks.

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Minzhi Chen ◽  
Fan Wu ◽  
Min Yin ◽  
Jiangang Xu

Planning of road networks is fundamental for public transportation. The impact of road network density on public transportation has been extensively studied, but few studies in this regard involved evaluation indicators for connectivity and layout of road networks. With 29 cities in China as the study cases, this paper quantifies the layout structure of the road network based on the network’s betweenness centralization and establishes a multivariate linear regression model to perform regression of the logarithm of the frequency of per capita public transportation on betweenness centralization. It is found in the present work that there is a significant correlation between the layout structure of an urban road network and the residents’ utilization degree of public transportation. A greater betweenness centralization of the urban road network, namely a more centralized road network, means a higher frequency of per capita public transportation of urban residents and a higher degree of the residents’ utilization of public transportation. In the development of public transportation, centralized and axial-shaped layout structures of road networks can be promoted to improve the utilization of public transportation.


Author(s):  
U. Feuerhake ◽  
O. Wage ◽  
M. Sester ◽  
N. Tempelmeier ◽  
W. Nejdl ◽  
...  

<p><strong>Abstract.</strong> Accurate predictions of the characteristics of urban streets in particular with respect to the typical traffic situations are crucial for numerous real world applications such as navigation, scheduling of logistic and public transportation services as well as high-level planning of infrastructure which may include planning of construction sites or even changes of the road topology. However, this information may be hard to obtain, especially in complex urban road networks where interdependencies between roads are highly present. In addition, accurate and recent traffic data is not always available, especially for uncommon situations like large-scale public events, traffic accidents or construction sites. This work demonstrates how to employ historical traffic datasets in conjunction with other, infrastructure related data, to derive a deeper understanding of urban traffic behaviour. In particular this paper provides the following contributions: (1) the generation of meaningful features to describe the segments in urban road networks; (2) an unsupervised machine learning approach that identifies similar segments based on those features; (3) a supervised approach to predict unknown features of the segments and, finally, (4) an extensive evaluation of the extracted road characteristics and the proposed methods using real-world data. The resulting clusters reveal the similarities of the street segments and give a different perspective on the road network and the traffic situation, respectively. The experiments on the classification approach demonstrate that unknown features can be predicted with a good quality.</p>


2012 ◽  
Vol 253-255 ◽  
pp. 1922-1929
Author(s):  
Jian Cheng Weng ◽  
Wen Jie Zou ◽  
Jian Rong

In order to better identify the spatial influence between adjacent parts of road networks, the paper introduces the spatial autocorrelation theory in evaluating the operation performance of urban road networks. The research proposes several spatial correlation validation indicators to verify the spatial characteristics among the road networks. Based on the analysis of spatial characteristics, the relationship between operation performance and influencing factors under the impact of spatial effect is examined. Furthermore, a spatial autocorrelation based influence models at three traffic flow levels is developed by using the data from a partial urban road network in Beijing. The model analysis shows that the spatial autocorrelation model is more effective in analyzing the urban road network operation performance under the influence of various factors. This model will be beneficial in identifying traffic network problems and improving traffic operations of the urban road network.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Huaikun Xiang

The vulnerability of an urban road network is affected by many factors, such as internal road network layout, network structure strength, and external destructive events, which have great uncertainty and complexity. Thus, there is still no unified and definite vulnerability analysis scheme available to cities. This paper proposes an integrative vulnerability identification method for urban road networks, which mainly relates to the vulnerability connotation and characteristics analysis of urban road networks during emergency, and vulnerability comprehensive evaluation indices design based on urban road network connectivity, traffic efficiency and performance, and an empirical study on a vulnerability identification method of an urban road network. In the empirical case, a real road network and traffic operation data were used from Science and Technology Park of Shenzhen City, China. In the context of one certain emergency scenario, the stated preference survey method and maximum likelihood method are used to solve the road users’ random travel choice behavior parameters; subsequently, based on the traffic equilibrium distribution prediction, the traffic vulnerability identification methods of the road network in this region were verified before and after the emergency. The method presented here not only considers the impact of network topology changes on road network traffic function during emergency but also considers the impact of dynamic changes in road network traffic demand on vulnerability; therefore, it is closer to the actual distribution of urban road network traffic vulnerability.


2013 ◽  
Vol 756-759 ◽  
pp. 1234-1239
Author(s):  
Yan Ling Zheng

Proposed a new index structure, named MG2R*, can efficiently store and retrieve the past, present and future positions of network-constrained moving objects. It is a two-tier structure. The upper is a MultiGrid-R*-Tree (MGRT for short) that is used to index the road network. The lower is a group of independent R*-Tree. Each R*-Tree is relative to a route in the road network, can index the spatiotemporal trajectory of the moving objects in the road. Moreover, moving objects query is implemented based on this index structure. It compared to other index structures for road-network-based moving objects, such as MON-Tree, the experimental results shown that the MG2R* can effectively improve the query performance of the spatio-temporal trajectory of network-constrained moving objects.


2019 ◽  
Vol 272 ◽  
pp. 01038
Author(s):  
C Withanage ◽  
D Lakmal ◽  
M Hansini ◽  
K Kankanamge ◽  
Y Witharanage ◽  
...  

In today’s world, the traffic volume on urban road networks is multiplying rapidly due to the heavy usage of vehicles and mobility on demand services. Migration of people towards urban areas result in increasing size and complexity of urban road networks. When handling such complex traffic systems, partitioning the road network into multiple sub-regions and managing the identified sub regions is a popular approach. In this paper, we propose an algorithm to identify sub-regions of a road network that exhibit homogeneous traffic flow patterns. In a stage wise manner, we model the road network graph by using taxi-trip data obtained on the selected region. Then, we apply the proposed modified multilevel kway partitioning algorithm to obtain optimal number of partitions from the developed road graph. An interesting feature of this algorithm is, resulting partitions are geographically connected and consists minimal interpartition trip flow. Our results show that the proposed algorithm outperforms state-of-the-art multilevel partitioning algorithms for tripbased road networks. By this research, we demonstrate the ability of road network partitioning using trip data while preserving the partition homogeneity and connectivity.


2019 ◽  
Vol 11 (19) ◽  
pp. 5307 ◽  
Author(s):  
Shiguang Wang ◽  
Dexin Yu ◽  
Mei-Po Kwan ◽  
Huxing Zhou ◽  
Yongxing Li ◽  
...  

Understanding the evolution and growth patterns of urban road networks helps to design an efficient and sustainable transport network. The paper proposed a general study framework and analytical workflow based on network theory that could be applied to almost any city to analyze the temporal evolution of road networks. The main tasks follow three steps: vector road network drawing, topology graph generation, and measure classification. Considering data availability and the limitations of existing studies, we took Changchun, China, a middle-sized developing city that is seldom reported in existing studies, as the study area. The research results of Changchun (1912–2017) show the road networks sprawled and densified over time, and the evolution patterns depend on the historical periods and urban planning modes. The evolution of network scales exhibits significant correlation; the population in the city is well correlated with the total road length and car ownership. Each network index also presents specific rules. All road networks are small-world networks, and the arterial roads have been consistent over time; however, the core area changes within the adjacent range but is generally far from the old city. More importantly, we found the correlation between structure and function of the urban road networks in terms of the temporal evolution. However, the temporal evolution pattern shows the correlation varies over time or planning modes, which had not been reported


2021 ◽  
pp. 67-80
Author(s):  
Mukhammad Rizka Fahmi Amrozi ◽  
Raihan Pasha Isheka

An Urban Road network is often used for multipurpose trips, due to their transportation functions, such as attractiveness and orientation, as well as social, ecological, and economic features. In Indonesia, road incidents have reportedly increased during the last decade because of a higher frequency of natural hazards, accidents, and on-street mass demonstrations. These incidents are found to degrade or terminate road access, forcing users to utilize alternative routes and decreasing the service performance in adjacent directions. Due to the unexpected occurrences at any location and time, there is a need to investigate the impact of random incidents on road performances. Several accessibility indexes have also been used to evaluate the vulnerability of road networks. However, this is less practical in Indonesia, with the road authority using functional performances as the indicator. This indicates the need for an index to be developed based on road performance parameters. Therefore, this study aims to develop a road performance-based vulnerability index known as the RCI (Road Criticality Index). Combined with a traffic simulation tool, this system is used as an alternative index to assess vulnerabilities, by identifying the road(s) providing worse consequences due to unforeseen incidents. This simulation was conducted by using the PTV Visum, assuming a road section is closed due to the worst incident scenarios. The result showed that the RCI offered a more comprehensive assessment than the existing indicator (volume capacity ratio). The RCI included travel speed and mobility components for evaluating both local and global road performances. With the knowledge of the most vulnerable locations and their consequences, road authorities can prioritize maintenance and development strategies based on the criticality index. Also, preventive measures should be conducted to mitigate risk under a constrained budget. This methodology can be applied to sustainably enhance the resilience of urban road networks.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Lin Gao ◽  
Mingzhen Wang ◽  
Anshuang Liu ◽  
Huafeng Gong

The road network’s transport capacity and traffic function will be directly reduced if urban roads are damaged by earthquakes. To effectively improve the resistance and recovery ability of urban road networks facing earthquake disasters, the establishment of an aseismic resilience evaluation method for the urban road network is the research goal. This paper’s novelty introduces the concept of engineering resilience into the aseismic performance evaluation of urban road networks. It reveals the internal influence principle of nodes and independent pathways on the aseismic resilience of the network. This paper’s significant contribution is to establish a reasonable and comprehensive urban road network aseismic resilience evaluation method. This method can realize the calculation of the aseismic resilience for the existing network, reconstruction network, and new network and propose the optimization, transformation, and layout for the network. The MATLAB program for the whole process calculation of aseismic resilience is developed. The overall network’s aseismic resilience is obtained by the sum of the product of the node importance and the average number of the reliable independent pathways.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tinggui Chen ◽  
Shiwen Wu ◽  
Jianjun Yang ◽  
Guodong Cong ◽  
Gongfa Li

It is common that many roads in disaster areas are damaged and obstructed after sudden-onset disasters. The phenomenon often comes with escalated traffic deterioration that raises the time and cost of emergency supply scheduling. Fortunately, repairing road network will shorten the time of in-transit distribution. In this paper, according to the characteristics of emergency supplies distribution, an emergency supply scheduling model based on multiple warehouses and stricken locations is constructed to deal with the failure of part of road networks in the early postdisaster phase. The detailed process is as follows. When part of the road networks fail, we firstly determine whether to repair the damaged road networks, and then a model of reliable emergency supply scheduling based on bi-level programming is proposed. Subsequently, an improved artificial bee colony algorithm is presented to solve the problem mentioned above. Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.


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