Simulation of Emergency Evacuation of Pedestrians along the Road Networks in Nhatrang City

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation of a limited budget and avoiding excessive installation of safety facilities. To assess the safety risk of rural roadsides when the crash data are unavailable or missing, this study proposed a Bayesian Network (BN) method that uses the experts’ judgments on the conditional probability of different safety risk factors to evaluate the safety risk of rural roadsides. Eight factors were considered, including seven factors identified in the literature and a new factor named access point density. To validate the effectiveness of the proposed method, a case study was conducted using 19.42 km long road networks in the rural area of Nantong, China. By comparing the results of the proposed method and run-off-road (ROR) crash data from 2015–2016 in the study area, the road segments with higher safety risk levels identified by the proposed method were found to be statistically significantly correlated with higher crash severity based on the crash data. In addition, by comparing the respective results evaluated by eight factors and seven factors (a new factor removed), we also found that access point density significantly contributed to the safety risk of rural roadsides. These results show that the proposed method can be considered as a low-cost solution to evaluating the safety risk of rural roadsides with relatively high accuracy, especially for areas with large rural road networks and incomplete ROR crash data due to budget limitation, human errors, negligence, or inconsistent crash recordings.

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Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters

Complexity ◽

10.1155/2020/7501891 ◽

2020 ◽

Vol 2020 ◽

pp. 1-15 ◽

Cited By ~ 12

Author(s):

Tinggui Chen ◽

Shiwen Wu ◽

Jianjun Yang ◽

Guodong Cong ◽

Gongfa Li

Keyword(s):

Road Network ◽

Road Networks ◽

Sudden Onset ◽

The Road ◽

Bee Colony ◽

Proposed Model ◽

Effectiveness And Efficiency ◽

In Transit ◽

Emergency Supply

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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Capacity in municipalities: Infrastructures, maintenance debts and ways of overcoming a run-to-failure mentality

Local Economy The Journal of the Local Economy Policy Unit ◽

10.1177/02690942211030475 ◽

2021 ◽

pp. 026909422110304

Author(s):

Jens Alm ◽

Alexander Paulsson ◽

Robert Jonsson

Keyword(s):

Economies Of Scale ◽

Heavy Traffic ◽

Road Networks ◽

Large Degree ◽

Welfare States ◽

The Road ◽

Technical Capacity ◽

Multidimensional Concept ◽

Sewage Systems ◽

Road Segments

There is a growing maintenance debt of ageing and critical infrastructures in many municipalities in European welfare states. In this article, we use the multidimensional concept of local capacity as a point of departure to analyse how and in what ways Swedish municipalities work with the routine maintenance of infrastructures, including municipal road networks as well as water and sewage systems. For the road networks, maintenance is generally outsourced to contractors and there is also a large degree of tolerance for various standards on different road segments within and between the municipalities. Less used road segments are not as prioritised as those with heavy traffic. For the water and sewage systems, in-house technical capacity is needed as differences in water quality are not tolerated. Economies of scale mean that in-house capacity is translated into the creation of inter-municipal bodies. As different forms of capacities tend to reinforce each other, municipal capacity builds up over time in circular movements. These results add knowledge to current research by pointing to the ways municipalities are overcoming a run-to-failure mentality by building capacity to pay off the infrastructural maintenance debt.

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Design of Optimal Rainfall Monitoring Network Using Radar and Road Networks

Entropy ◽

10.3390/e23030378 ◽

2021 ◽

Vol 23 (3) ◽

pp. 378

Author(s):

Taeyong Kwon ◽

Seongsim Yoon ◽

Sanghoo Yoon

Keyword(s):

Road Networks ◽

Monitoring Network ◽

Conditional Entropy ◽

Radar Data ◽

Disaster Risk ◽

Water Levels ◽

The Road ◽

Dam Operation ◽

A Site ◽

High Degree

Uncertainty in the rainfall network can lead to mistakes in dam operation. Sudden increases in dam water levels due to rainfall uncertainty are a high disaster risk. In order to prevent these losses, it is necessary to configure an appropriate rainfall network that can effectively reflect the characteristics of the watershed. In this study, conditional entropy was used to calculate the uncertainty of the watershed using rainfall and radar data observed from 2018 to 2019 in the Goesan Dam and Hwacheon Dam watersheds. The results identified radar data suitable for the characteristics of the watershed and proposed a site for an additional rainfall gauge. It is also necessary to select the location of the additional rainfall gauged by limiting the points where smooth movement and installation, for example crossing national borders, are difficult. The proposed site emphasized accessibility and usability by leveraging road information and selecting a radar grid near the road. As a practice result, the uncertainty of precipitation in the Goesan and Hwacheon Dam watersheds could be decreased by 70.0% and 67.9%, respectively, when four and three additional gauge sites were installed without any restriction. When these were installed near to the road, with five and four additional gauge sites, the uncertainty in the Goesan Dam and Hwacheon Dam watersheds were reduced by up to 71.1%. Therefore, due to the high degree of uncertainty, it is necessary to measure precipitation. The operation of the rainfall gauge can provide a smooth site and configure an appropriate monitoring network.

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A Parallel-Computing Approach for Vector Road-Network Matching Using GPU Architecture

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi7120472 ◽

2018 ◽

Vol 7 (12) ◽

pp. 472 ◽

Cited By ~ 1

Author(s):

Bo Wan ◽

Lin Yang ◽

Shunping Zhou ◽

Run Wang ◽

Dezhi Wang ◽

...

Keyword(s):

Road Network ◽

Large Scale ◽

Graphics Processing Unit ◽

Road Networks ◽

Processing Unit ◽

Data Partition ◽

Matching Method ◽

The Road ◽

Central Processing ◽

Relaxation Matching

The road-network matching method is an effective tool for map integration, fusion, and update. Due to the complexity of road networks in the real world, matching methods often contain a series of complicated processes to identify homonymous roads and deal with their intricate relationship. However, traditional road-network matching algorithms, which are mainly central processing unit (CPU)-based approaches, may have performance bottleneck problems when facing big data. We developed a particle-swarm optimization (PSO)-based parallel road-network matching method on graphics-processing unit (GPU). Based on the characteristics of the two main stages (similarity computation and matching-relationship identification), data-partition and task-partition strategies were utilized, respectively, to fully use GPU threads. Experiments were conducted on datasets with 14 different scales. Results indicate that the parallel PSO-based matching algorithm (PSOM) could correctly identify most matching relationships with an average accuracy of 84.44%, which was at the same level as the accuracy of a benchmark—the probability-relaxation-matching (PRM) method. The PSOM approach significantly reduced the road-network matching time in dealing with large amounts of data in comparison with the PRM method. This paper provides a common parallel algorithm framework for road-network matching algorithms and contributes to integration and update of large-scale road-networks.

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Road Networks Winter Risk Estimation Using On-Board Uncooled Infrared Camera for Surface Temperature Measurements over Two Lanes

International Journal of Geophysics ◽

10.1155/2011/514970 ◽

2011 ◽

Vol 2011 ◽

pp. 1-8 ◽

Cited By ~ 3

Author(s):

M. Marchetti ◽

M. Moutton ◽

S. Ludwig ◽

L. Ibos ◽

V. Feuillet ◽

...

Keyword(s):

Data Analysis ◽

Road Network ◽

Risk Estimation ◽

Risk Index ◽

Road Networks ◽

Infrared Camera ◽

Atmospheric Parameters ◽

The Road ◽

Measurement Rate

Thermal mapping has been implemented since the late eighties to establish the susceptibility of road networks to ice occurrence with measurements from a radiometer and some atmospheric parameters. They are usually done before dawn during wintertime when the road energy is dissipated. The objective of this study was to establish if an infrared camera could improve the determination of ice road susceptibility, to build a new winter risk index, to improve the measurements rate, and to analyze its consistency with seasons and infrastructures environment. Data analysis obtained from the conventional approved radiometer sensing technique and the infrared camera has shown great similarities. A comparison was made with promising perspectives. The measurement rate to analyse a given road network could be increased by a factor two.

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Comparing the road networks of residential areas

Pollack Periodica ◽

10.1556/606.2016.11.3.6 ◽

2016 ◽

Vol 11 (3) ◽

pp. 61-72 ◽

Cited By ~ 1

Author(s):

Andor Háznagy ◽

István Fi

Keyword(s):

Road Networks ◽

Residential Areas ◽

The Road

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Impact of Road Network Topology on Public Transportation Development

Wireless Communications and Mobile Computing ◽

10.1155/2021/6209592 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Minzhi Chen ◽

Fan Wu ◽

Min Yin ◽

Jiangang Xu

Keyword(s):

Public Transportation ◽

Road Network ◽

Road Networks ◽

Urban Road Network ◽

Urban Road ◽

The Road ◽

Layout Structure ◽

Per Capita ◽

Transportation Development ◽

The Impact

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.

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