scholarly journals Hub-Periphery Hierarchy in Bus Transportation Networks: Gini Coefficients and the Seoul Bus System

2020 ◽  
Vol 12 (18) ◽  
pp. 7297 ◽  
Author(s):  
Chansoo Kim ◽  
Segun Goh ◽  
Myeong Seon Choi ◽  
Keumsook Lee ◽  
M. Y. Choi
Keyword(s):  
Gini Coefficient ◽  
City Planning ◽  
Transportation Networks ◽  
Transportation Network ◽  
Growth Dynamics ◽  
Transportation Systems ◽  
The Gini Coefficient ◽  
Bus Stops ◽  
Bus System ◽  
Bus Transportation

Bus transportation networks are characteristically different from other mass transportation systems such as airline or subway networks, and thus the usual approach may not work properly. In this paper, to analyze the bus transportation network, we employ the Gini coefficient, which measures the disparity of weights of bus stops. Applied to the Seoul bus system specifically, the Gini coefficient allows us to classify nodes in the bus network into two distinct types: hub and peripheral nodes. We elucidate the structural properties of the two types in the years 2011 and 2013, and probe the evolution of each type over the two years. It is revealed that the hub type evolves according to the controlled growth process while the peripheral one, displaying a number of new constructions as well as sudden closings of bus stops, is not described by growth dynamics. The Gini coefficient thus provides a key mathematical criterion of decomposing the transportation network into a growing one and the other. It would also help policymakers to deal with the complexity of urban mobility and make more sustainable city planning.

scholarly journals Deep Autoencoder Neural Networks for Short-Term Traffic Congestion Prediction of Transportation Networks

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2229 ◽  
Author(s):  
Sen Zhang ◽  
Yong Yao ◽  
Jie Hu ◽  
Yong Zhao ◽  
Shaobo Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Large Scale ◽  
Transportation Networks ◽  
Transportation Network ◽  
Transportation Systems ◽  
Neural Network Models ◽  
Computation Efficiency ◽  
Congestion Prediction

Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow we create a dataset named Seattle Area Traffic Congestion Status (SATCS) based on traffic congestion map snapshots from a publicly available online traffic service provider Washington State Department of Transportation. We then propose a deep autoencoder-based neural network model with symmetrical layers for the encoder and the decoder to learn temporal correlations of a transportation network and predicting traffic congestion. Our experimental results on the SATCS dataset show that the proposed DCPN model can efficiently and effectively learn temporal relationships of congestion levels of the transportation network for traffic congestion forecasting. Our method outperforms two other state-of-the-art neural network models in prediction performance, generalization capability, and computation efficiency.

scholarly journals Bus transport network analysis in Rio de Janeiro based on topological models using Social Networks

2020 ◽  
Author(s):  
Diego Carvalho ◽  
Rafael Barbastefano ◽  
Louise Pumar
Keyword(s):  
Social Networks ◽  
Rio De Janeiro ◽  
Transportation Network ◽  
Giant Component ◽  
Space Networks ◽  
Minimum Number ◽  
Bus Stops ◽  
Bus Networks ◽  
Topological Models ◽  
Bus System

In recent years, studies on public transport networks have intensified in the Social Networks field, especially in bus networks, motivated by urban mobility’s relevance for the proper functioning of a city. Rio de Janeiro city, Brazil, has undergone recent changes in its municipal bus system, modifying several lines and bus stops due to the preparation for the Olympic games. This paper analyzes the structure of Rio’s bus transportation network of this city using Social Network technics, comparing its topology in 2014 and 2016 – before and after the change and the properties of the bus system investigated based on the topological models B-space, P-space, and C-space. Some essential parameters were calculated, such as giant component, distance, diameter, degree, closeness, and betweenness. The results showed a reduction of 22.75% of the lines and 5.19% of the bus stops from 2014 to 2016. We show that a maximum of four lines is required to move between any two bus stops within the city in both years. However, with three, it is possible to reach more than 99% of the bus stops. Besides, this study also introduces a new C- space network according to the minimum number of frequent bus stops that the lines had. Based on the giant component analysis of these new C-space networks with many common points, it is possible to detect possible expressway corridors.

scholarly journals Dynamic measures for transportation networks

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0242875
Author(s):  
Oriol Lordan ◽  
Jose M. Sallan
Keyword(s):  
Transportation Networks ◽  
Low Cost ◽  
Transportation Network ◽  
Waiting Times ◽  
Shortest Paths ◽  
Dynamic Network ◽  
Transportation Systems ◽  
Accurate Information ◽  
Network Analyses ◽  
Dynamic Representation

Most complex network analyses of transportation systems use simplified static representations obtained from existing connections in a time horizon. In static representations, travel times, waiting times and compatibility of schedules are neglected, thus losing relevant information. To obtain a more accurate description of transportation networks, we use a dynamic representation that considers synced paths and that includes waiting times to compute shortest paths. We use the shortest paths to define dynamic network, node and edge measures to analyse the topology of transportation networks, comparable with measures obtained from static representations. We illustrate the application of these measures with a toy model and a real transportation network built from schedules of a low-cost carrier. Results show remarkable differences between measures of static and dynamic representations, demonstrating the limitations of the static representation to obtain accurate information of transportation networks.

Transportation Development in Indochina

1996 ◽  
Vol 1563 (1) ◽  
pp. 41-47 ◽  
Author(s):  
Yuichiro Motomura
Keyword(s):  
Transportation Networks ◽  
Transportation Network ◽  
Transportation Systems ◽  
Mekong River ◽  
Viet Nam ◽  
The West ◽  
The Past ◽  
To Come ◽  
Transportation Development ◽  
First Time

For the first time in history the three countries in Indochina—Cambodia, Laos, and Viet Nam—have started a massive effort to upgrade their transportation systems, particularly those linking each one to the others. Despite the fact that the great Mekong River runs through all three countries, natural barriers formed by the massive Annamite Mountains, which extend from the Himalayas, effectively divide the peninsula, preventing both the Chinese civilization from the east and the Indian civilization from the west from crossing the barrier. Such seclusion suited the region's socialist regimes well in the 1970s and 1980s. Since the 1990s, however, circumstances have induced these three countries to adopt more market-oriented and outward-looking policies, which created interest in expanding and strengthening the region's transportation network. In addition to the drawing up of plans for domestic transportation networks, frequent international conferences have been convened to seek cooperation among the Indochinese countries and from abroad. Many projects have been identified, and some are being implemented. The extreme neglect under which the transportation network has operated during the past two decades has made such efforts daunting. The task of upgrading transportation infrastructure in Indochina will be a priority for some time to come.

Application of Accident Prediction Models for Computation of Accident Risk on Transportation Networks

2002 ◽  
Vol 1784 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Dominique Lord
Keyword(s):  
Traffic Flow ◽  
Prediction Models ◽  
Transportation Networks ◽  
Transportation Network ◽  
Transportation Systems ◽  
Primary Objective ◽  
Individual Risk ◽  
Original Research ◽  
Accident Risk ◽  
Accident Prediction

Accident risk has been applied extensively in transportation safety analysis. Risk is often used to describe the level of safety in transportation systems by incorporating a measure of exposure, such as traffic flow or kilometers driven. The most commonly applied definition of accident risk states that risk is a linear function of accidents and traffic flow. This definition, however, creates problems for transportation systems that are characterized by a nonlinear relationship between these variables. The primary objective of the original research was to illustrate the application of accident prediction models (APMs) to estimate accident risk on transportation networks. (APMs are useful tools for establishing the proper relationship between accidents and traffic flow.) The secondary objective was to describe important issues and limitations surrounding the application of APMs for this purpose. To accomplish these objectives, APMs were applied to a computerized transportation network with the help of EMME/2. The accident risk was computed with the traffic flow output of the computer program. The results were dramatic and unexpected: in essence, the individual risk of being involved in a collision decreases as traffic flow increases. The current and most common model form of APMs explains this outcome. The application of these results may have significant effects on transportation policy and intelligent transportation system strategies.

scholarly journals Evaluation of Microsimulation Models for Roadway Segments with Different Functional Classifications in Northern Iran

2021 ◽  
Vol 6 (3) ◽  
pp. 46
Author(s):  
Amir Masoud Rahimi ◽  
Maxim A. Dulebenets ◽  
Arash Mazaheri
Keyword(s):  
Intelligent Transportation Systems ◽  
Network Performance ◽  
Traffic Simulation ◽  
Transportation Networks ◽  
Transportation Network ◽  
Travel Speed ◽  
Transportation Systems ◽  
Mitigation Strategies ◽  
Northern Iran ◽  
Microsimulation Models

Industrialization, urban development, and population growth in the last decades caused a significant increase in congestion of transportation networks across the world. Increasing congestion of transportation networks and limitations of the traditional methods in analyzing and evaluating the congestion mitigation strategies led many transportation professionals to the use of traffic simulation techniques. Nowadays, traffic simulation is heavily used in a variety of applications, including the design of transportation facilities, traffic flow management, and intelligent transportation systems. The literature review, conducted as a part of this study, shows that many different traffic simulation packages with various features have been developed to date. The present study specifically focuses on a comprehensive comparative analysis of the advanced interactive microscopic simulator for urban and non-urban networks (AIMSUN) and SimTraffic microsimulation models, which have been widely used in the literature and practice. The evaluation of microsimulation models is performed for the four roadway sections with different functional classifications, which are located in the northern part of Iran. The SimTraffic and AIMSUN microsimulation models are compared in terms of the major transportation network performance indicators. The results from the conducted analysis indicate that AIMSUN returned smaller errors for the vehicle flow, travel speed, and total travel distance. On the other hand, SimTraffic provided more accurate values of the travel time. Both microsimulation models were able to effectively identify traffic bottlenecks. Findings from this study will be useful for the researchers and practitioners, who heavily rely on microsimulation models in transportation planning.

Protecting public health and global freight transportation systems during an influenza pandemic

2008 ◽  
Vol 3 (2) ◽  
pp. 99-107 ◽  
Author(s):  
Thomas C. Luke, MD ◽  
Jean-Paul Rodrigue, PhD
Keyword(s):  
Public Health ◽  
Pandemic Influenza ◽  
Transportation Networks ◽  
Transportation Network ◽  
Influenza Pandemic ◽  
Transportation Systems ◽  
Prevention Measures ◽  
Transportation Industry ◽  
H5n1 Influenza ◽  
Health Support

The H5N1 influenza threat is resulting in global preparations for the next influenza pandemic. Pandemic influenza planners are prioritizing scarce vaccine, antivirals, and public health support for different segments of society. The freight, bulk goods, and energy transportation network comprise the maritime, rail, air, and trucking industries. It relies on small numbers of specialized workers who cannot be rapidly replaced if lost due to death, illness, or voluntary absenteeism. Because transportation networks link economies, provide critical infrastructures with working material, and supply citizens with necessary commodities, disrupted transportation systems can lead to cascading failures in social and economic systems. However, some pandemic influenza plans have assigned transportation workers a low priority for public health support, vaccine, and antivirals. The science of Transportation Geography demonstrates that transportation networks and workers are concentrated at, or funnel through, a small number of chokepoints and corridors. Chokepoints should be used to rapidly and efficiently vaccinate and prophylax the transportation worker cohort and to implement transmission prevention measures and thereby protect the ability to move goods. Nations, states, the transportation industry and unions, businesses, and other stakeholders must plan, resource, and exercise, and then conduct a transportation health assurance and security campaign for an influenza pandemic.

scholarly journals Radiation Effect of Urban Agglomeration’s Transportation Network: Evidence from Chengdu–Chongqing Urban Agglomeration, China

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 520
Author(s):  
Zhangfeng Yao ◽  
Kunhui Ye ◽  
Liang Xiao ◽  
Xiaowei Wang
Keyword(s):  
Field Strength ◽  
Radiation Effects ◽  
Radiation Effect ◽  
Transportation Networks ◽  
Transportation Network ◽  
Transportation Systems ◽  
Urban Agglomeration ◽  
Strength Model ◽  
The Core ◽  
Stable Pattern

Recent years have seen the global proliferation and integration of transportation systems in urban agglomeration (UA), suggesting that transportation networks have become more prominent in the sustainable development of UA. Core cities play a radiating and driving role in affecting their adjacent cities to formulate transportation networks. Such a phenomenon is called the radiation effect of transportation networks and can be imaged using a field strength model as proposed in the study. The field strength model was verified using the Chengdu–Chongqing urban agglomeration (CCUA) as a case. Case data concerning transportation routes and traffic volume were collected for the past 20 years. The data analyses results indicate a relatively stable pattern of transportation networks in the UA. UA cities’ radiation effects follow the same compactness trend. The core cities’ radiation spheres go beyond their territories, and they can envelop the surrounding cities, highlighting the core cities’ dominance in the entire transportation network. Moreover, two development stages of UA transportation—focus and spillover—are also identified. This study contributes to the literature by providing an innovative quantitative method to detect the interaction between a city’s transportation system and peripheral cities or regions. The radiation effect of cities’ transportation systems should be considered in the UA transportation development plan, so as to meet the needs of spatial structure planning and coordinated development of the UA.

Best Neighbor Heuristic Search for Finding Minimum Paths in Transportation Networks

1998 ◽  
Vol 1651 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Jeffrey L. Adler
Keyword(s):  
Heuristic Search ◽  
Transportation Networks ◽  
Transportation Network ◽  
Search Problems ◽  
A Algorithm ◽  
Running Time ◽  
Search Effort ◽  
Wide Range ◽  
Path Search ◽  
Sparse Networks

For a wide range of transportation network path search problems, the A* heuristic significantly reduces both search effort and running time when compared to basic label-setting algorithms. The motivation for this research was to determine if additional savings could be attained by further experimenting with refinements to the A* approach. We propose a best neighbor heuristic improvement to the A* algorithm that yields additional benefits by significantly reducing the search effort on sparse networks. The level of reduction in running time improves as the average outdegree of the network decreases and the number of paths sought increases.

Sign in / Sign up

Export Citation Format

Share Document