scholarly journals IMPACT OF GAP FILLING ON QUALITY OF ROAD NETWORKS

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 683-686
Author(s):  
M. Maboudi ◽  
J. Amini ◽  
M. Gerke
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Quality Criteria ◽  
Tensor Voting ◽  
Road Extraction ◽  
Gap Filling ◽  
The Road ◽  
Geometrical Quality ◽  
On The Road

Abstract. High quality and updated road network maps provide important information for many domains. Many small segments appear on the road surface in VHR images. Most road extraction systems have problem in extraction of these small segments and usually they appear as gaps in the final extracted road networks. However, most approaches skip filling these gaps. This is on account of the fact that usually overall length of the missing parts of the road extraction results is very short relative to the total length of the whole road network. This leads to an indiscernible impact of filling these gaps on geometrical quality criteria. In this paper, using two different VHR satellite datasets and a gap-filling approach which is based on tensor voting, we show that utilizing an effective road gap filling can result in a quite tangible topological improvement in the final road network which is highly demanded in many applications.

scholarly journals AUTOMATIC EXTRACTION OF ROAD CENTERLINES AND EDGE LINES FROM AERIAL IMAGES VIA CNN-BASED REGRESSION

2020 ◽  
Vol V-2-2020 ◽  
pp. 925-932
Author(s):  
Y. Wei ◽  
X. Hu ◽  
M. Zhang ◽  
Y. Xu
Keyword(s):  
Road Network ◽  
Aerial Images ◽  
Automatic Extraction ◽  
Tensor Voting ◽  
Road Extraction ◽  
The Road ◽  
Road Width ◽  
Road Intersections ◽  
On The Road ◽  
Segmentation Problem

Abstract. Extracting roads from aerial images is a challenging task in the field of remote sensing. Most approaches formulate road extraction as a segmentation problem and use thinning and edge detection to obtain road centerlines and edge lines, which could produce spurs around the extracted centerlines/edge lines. In this study, a novel regression-based method is proposed to extract road centerlines and edge lines directly from aerial images. The method consists of three major steps. First, an end-to-end regression network based on CNN is trained to predict confidence maps for road centerlines and estimate road width. Then, after the CNN predicts the confidence map, non-maximum suppression and road tracking are applied to extract accurate road centerlines and construct road topology. Meanwhile, Road edge lines are generated based on the road width estimated by the CNN. Finally, in order to improve the connectivity of extracted road network, tensor voting is applied to detect road intersections and the detected intersections are used as guidance for the overcome of discontinuities. The experiments conducted on the SpaceNet and DeepGlobe datasets show that our approach achieves better performance than other methods.

scholarly journals Analysis of Traffic Evolution on Road Networks of a Roundabout

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Tolesa Hundesa Muleta ◽  
Legesse Lemecha Obsu
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Road Networks ◽  
Point Of View ◽  
Traffic Dynamics ◽  
Demand And Supply ◽  
The Road ◽  
On The Road ◽  
Detailed Mathematical Analysis ◽  
Control Traffic

In this paper, the analyses of traffic evolution on the road network of a roundabout having three entrances and three exiting legs are conducted from macroscopic point of view. The road networks of roundabouts are modeled as a merging and diverging types 1×2 and 2×1 junctions. To study traffic evolution at junction, two cases have been considered, namely, demand and supply limited cases. In each case, detailed mathematical analysis and numerical tests have been presented. The analysis in the case of demand limited showed that rarefaction wave fills the portion of the road network in time. In the contrary, in supply limited case, traffic congestion occurs at merging junctions and shock wave propagating back results in reducing the performance of a roundabout to control traffic dynamics. Also, we illustrate density and flux profiles versus space discretization at different time steps via numerical simulation with the help of Godunov scheme.

scholarly journals Road Topology Refinement via a Multi-Conditional Generative Adversarial Network

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1162
Author(s):  
Yang Zhang ◽  
Xiang Li ◽  
Qianyu Zhang
Keyword(s):  
Road Network ◽  
Rapid Development ◽  
Road Networks ◽  
Extraction Methods ◽  
Road Extraction ◽  
Generative Adversarial Network ◽  
Topological Information ◽  
The Road ◽  
Adversarial Network ◽  
Spectral Performance

With the rapid development of intelligent transportation, there comes huge demands for high-precision road network maps. However, due to the complex road spectral performance, it is very challenging to extract road networks with complete topologies. Based on the topological networks produced by previous road extraction methods, in this paper, we propose a Multi-conditional Generative Adversarial Network (McGAN) to obtain complete road networks by refining the imperfect road topology. The proposed McGAN, which is composed of two discriminators and a generator, takes both original remote sensing image and the initial road network produced by existing road extraction methods as input. The first discriminator employs the original spectral information to instruct the reconstruction, and the other discriminator aims to refine the road network topology. Such a structure makes the generator capable of receiving both spectral and topological information of the road region, thus producing more complete road networks compared with the initial road network. Three different datasets were used to compare McGan with several recent approaches, which showed that the proposed method significantly improved the precision and recall of the road networks, and also worked well for those road regions where previous methods could hardly obtain complete structures.

CREATING WALKING LED TRANSIT STATIONS FOR WOMEN IN MALAYSIA

2020 ◽  
Vol 7 (1) ◽  
pp. 99
Author(s):  
Yong Adilah Shamsul Harumain ◽  
Nur Farhana Azmi ◽  
Suhaini Yusoff
Keyword(s):  
Quality Of Life ◽  
Developing Countries ◽  
Public Transportation ◽  
Carbon Emission ◽  
The Other ◽  
Walking Distance ◽  
The Road ◽  
On The Road ◽  
Female User

Transit stations are generally well known as nodes of spaces where percentage of people walking are relatively high. The issue is do more planning is actually given to create walkability. Creating walking led transit stations involves planning of walking distance, providing facilities like pathways, toilets, seating and lighting. On the other hand, creating walking led transit station for women uncover a new epitome. Walking becomes one of the most important forms of mobility for women in developing countries nowadays. Encouraging women to use public transportation is not just about another effort to promote the use of public transportation but also another great endeavour to reduce numbers of traffic on the road. This also means, creating an effort to control accidents rate, reducing carbon emission, improving health and eventually, developing the quality of life. Hence, in this paper, we sought first to find out the factors that motivate women to walk at transit stations in Malaysia. A questionnaire survey with 562 female user of Light Railway Transit (LRT) was conducted at LRT stations along Kelana Jaya Line. Both built and non-built environment characteristics, particularly distance, safety and facilities were found as factors that are consistently associated with women walkability. With these findings, the paper highlights the criteria  which are needed to create and make betterment of transit stations not just for women but also for walkability in general.

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

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
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.

scholarly journals Politics, industry, and tourism: The conceptual construction of the blue highway

2020 ◽  
pp. 002252662097950
Author(s):  
Fredrik Bertilsson
Keyword(s):  
Road Network ◽  
Power Plants ◽  
Community Building ◽  
Atlantic Coast ◽  
Political Agenda ◽  
The Road ◽  
Conceptual Construction ◽  
On The Road ◽  
Post War

This article contributes to the research on the expansion of the Swedish post-war road network by illuminating the role of tourism in addition to political and industrial agendas. Specifically, it examines the “conceptual construction” of the Blue Highway, which currently stretches from the Atlantic Coast of Norway, traverses through Sweden and Finland, and enters into Russia. The focus is on Swedish governmental reports and national press between the 1950s and the 1970s. The article identifies three overlapping meanings attached to the Blue Highway: a political agenda of improving the relationships between the Nordic countries, industrial interests, and tourism. Political ambitions of Nordic community building were clearly pronounced at the onset of the project. Industrial actors depended on the road for the building of power plants and dams. The road became gradually more connected with the view of tourism as the motor of regional development.

scholarly journals THE PENETRATION OF ENGINEERING BY ECONOMICS: McFADDEN AND THE TRANSFORMATION OF ROAD DEMAND ESTIMATION

2021 ◽  
Vol 43 (2) ◽  
pp. 262-278
Author(s):  
Ariane Dupont-Kieffer ◽  
Sylvie Rivot ◽  
Jean-Loup Madre
Keyword(s):  
Road Network ◽  
Road Construction ◽  
Demand Estimation ◽  
Demand Modeling ◽  
The Road ◽  
Collective Decisions ◽  
The Face ◽  
Decision Making Processes ◽  
On The Road ◽  
The 1960S

The golden age of road demand modeling began in the 1950s and flourished in the 1960s in the face of major road construction needs. These macro models, as well as the econometrics and the data to be processed, were provided mainly by engineers. A division of tasks can be observed between the engineers in charge of estimating the flows within the network and the transport economists in charge of managing these flows once they are on the road network. Yet the inability to explain their decision-making processes and individual drives gave some room to economists to introduce economic analysis, so as to better understand individual or collective decisions between transport alternatives. Economists, in particular Daniel McFadden, began to offer methods to improve the measure of utility linked to transport and to inform the engineering approach. This paper explores the challenges to the boundaries between economics and engineering in road demand analysis.

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

2018 ◽  
Vol 7 (12) ◽  
pp. 472 ◽  
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.

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

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
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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