scholarly journals Zero Traffic Conflict (ZTC) Road Networks with Concentric Traffic Paths

2021 ◽  
Author(s):  
Richard Tasgal ◽  
David Eichler
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Vehicular Traffic ◽  
Careful Selection ◽  
Traffic Loads ◽  
Traffic Conflict ◽  
Left Turns ◽  
Travel Distances ◽  
Selection Of

U-turns and left turns are sometimes forbidden even though it increases travel distances. The greater travel distances are sometimes outweighed by the improved movement through intersections due to there being fewer conflicting lanes of traffic. One can, further, forbid straight-throughs. Restricting a sufficient number of turns can make intersections free from crossing lanes of traffic (``zero traffic conflict,'' ``ZTC"), though there may still be merging lanes of traffic. It's possible to make \begin{it}all\end{it} intersections in a road \begin{it}network\end{it} ZTC. However, keeping all destinations accessible and travel distances moderate requires careful selection of allowed driving directions and turning directions. We demonstrate through numerical microscopic and macroscopic simulations that there are road networks and ranges of traffic loads for which, in comparison with conventional schemes, ZTC road network can carry approximately $50$\% more vehicular traffic without incurring gridlock.

scholarly journals Deep Graph Convolutional Networks for Accurate Automatic Road Network Selection

2021 ◽  
Vol 10 (11) ◽  
pp. 768
Author(s):  
Jing Zheng ◽  
Ziren Gao ◽  
Jingsong Ma ◽  
Jie Shen ◽  
Kang Zhang
Keyword(s):  
Road Network ◽  
Spatial Information ◽  
Road Networks ◽  
Selection Effect ◽  
Network Selection ◽  
Small Scale ◽  
Attention Networks ◽  
Convolutional Networks ◽  
Spatial Features ◽  
Selection Of

The selection of road networks is very important for cartographic generalization. Traditional artificial intelligence methods have improved selection efficiency but cannot fully extract the spatial features of road networks. However, current selection methods, which are based on the theory of graphs or strokes, have low automaticity and are highly subjective. Graph convolutional networks (GCNs) combine graph theory with neural networks; thus, they can not only extract spatial information but also realize automatic selection. Therefore, in this study, we adopted GCNs for automatic road network selection and transformed the process into one of node classification. In addition, to solve the problem of gradient vanishing in GCNs, we compared and analyzed the results of various GCNs (GraphSAGE and graph attention networks [GAT]) by selecting small-scale road networks under different deep architectures (JK-Nets, ResNet, and DenseNet). Our results indicate that GAT provides better selection of road networks than other models. Additionally, the three abovementioned deep architectures can effectively improve the selection effect of models; JK-Nets demonstrated more improvement with higher accuracy (88.12%) than other methods. Thus, our study shows that GCN is an appropriate tool for road network selection; its application in cartography must be further explored.

Afterword

2020 ◽  
pp. 680-683
Author(s):  
Janice L. Waldron ◽  
Stephanie Horsley ◽  
Kari K. Veblen
Keyword(s):  
Social Media ◽  
Media Use ◽  
Careful Selection ◽  
Social Media Use ◽  
Pedagogical Tools ◽  
The Future ◽  
User Data ◽  
Selection Of ◽  
Data Surface

We all feel the implications of the force of social media—for good and for ill—in our lives and in our professional world. At the time of this writing, Facebook continues with its struggle to “clean up its act” as more revelations surrounding breaches of trust and hacked user data surface in the news and various countries attempt to hold Facebook to account. Despite this, social media use continues to grow exponentially, and the potential for responsible, ethical, and transparent social media to transform the ways in which we interact with and learn from each other increase with it. As we wait to see what the future holds for social media in society, we are reminded once again that it is the careful selection of pedagogical tools such as social media, as well the guided awareness of the challenges and benefits of those tools, that remains constant, even as tools may change, disappear, or fall out of fashion.

scholarly journals The use of cement concrete pavements for roads, depending on climatic conditions

2019 ◽  
Vol 13 (3) ◽  
pp. 235-240
Author(s):  
Iryna Solonenko
Keyword(s):  
European Union ◽  
Statistical Models ◽  
Road Network ◽  
The European Union ◽  
Rational Selection ◽  
Cement Concrete ◽  
The Road ◽  
Road Pavement ◽  
Operational Characteristics ◽  
Selection Of

The development of road network infrastructure is an important component of the economic development of the European Union. Updating of the road network contributes to the integration of the economies of countries into a coherent whole. The road network provides the free movement of citizens, the movement of goods and the effective implementation of various services. The increase in the length of the road network leads to an increase in the financial and material costs necessary to ensure its maintenance and repair. One of the ways to reduce costs is by strengthening the physic-mechanical and operational characteristics of the pavement due to the widespread use of cement concrete. The quality of the pavement of cement concrete depends largely on the rational selection of its composition. This allows a significant increase in the durability of road pavement. The purpose of the research was: the development of recommendations for the rational selection of the composition of the road pavement material of cement concrete, aimed at upgrading longevity, and taking into account its frost resistance grade. According to the goal, the following tasks were developed: the analyses of the climatic zones in which the road network of the European Union is located; the development of a research plan, a selection of the response function and influence factors; the study of physico-mechanical and operational characteristics of the researched material of road pavement; on the basis of the obtained data, the calculation of the complex of experimental-statistical models, which describe the physico-mechanical and operational characteristics of the road pavement material; on the basis of experimental statistical models, a method was proposed for selecting the rational compositions of the cement concrete pavement road material depending on the conditions of its application. The results presented in the article can be used in engineering and scientific practice for the selection of road pavement from cement concrete for highways.

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.

Patterned Villagescapes and Road Networks in Ancient Southwestern Amazonia

2020 ◽  
pp. 1-15
Author(s):  
Sanna Saunaluoma ◽  
Justin Moat ◽  
Francisco Pugliese ◽  
Eduardo G. Neves
Keyword(s):  
Material Culture ◽  
Unmanned Aerial Vehicle ◽  
Spatial Planning ◽  
Road Network ◽  
Road Networks ◽  
Archaeological Sites ◽  
Remotely Sensed Imagery ◽  
Aerial Vehicle ◽  
Human Transport ◽  
Southwestern Amazonia

Our recent data, collected using remotely sensed imagery and unmanned aerial vehicle surveys, reveal the extremely well-defined patterning of archaeological plaza villages in the Brazilian Acre state in terms of size, layout, chronology, and material culture. The villages comprise various earthen mounds arranged around central plazas and roads that radiate outward from, or converge on, the sites. The roads connected the villages situated 2–10 km from each other in eastern Acre. Our study attests to the existence of large, sedentary, interfluvial populations sharing the same sociocultural identities, as well as structured patterns of movement and spatial planning in relation to operative road networks during the late precolonial period. The plaza villages of Acre show similarity with the well-documented communities organized by road networks in the regions of the Upper Xingu and Llanos de Mojos. Taking into consideration ethnohistorical and ethnographic evidence, as well as the presence of comparable archaeological sites and earthwork features along the southern margin of Amazonia, we suggest that the plaza villages of Acre were linked by an interregional road network to other neighboring territories situated along the southern Amazonian rim and that movement along roads was the primary mode of human transport in Amazonian interfluves.

Forest path condition monitoring based on crowd-based trajectory data analysis

2020 ◽  
pp. 1-18
Author(s):  
Francisco Arcas-Tunez ◽  
Fernando Terroso-Saenz
Keyword(s):  
Information Acquisition ◽  
Road Network ◽  
Road Networks ◽  
Trajectory Data ◽  
Country Road ◽  
Wide Range ◽  
Sport Activities ◽  
Path Condition ◽  
Spatio Temporal ◽  
The City

The development of Road Information Acquisition Systems (RIASs) based on the Mobile Crowdsensing (MCS) paradigm has been widely studied for the last years. In that sense, most of the existing MCS-based RIASs focus on urban road networks and assume a car-based scenario. However, there exist a scarcity of approaches that pay attention to rural and country road networks. In that sense, forest paths are used for a wide range of recreational and sport activities by many different people and they can be also affected by different problems or obstacles blocking them. As a result, this work introduces SAMARITAN, a framework for rural-road network monitoring based on MCS. SAMARITAN analyzes the spatio-temporal trajectories from cyclists extracted from the fitness application Strava so as to uncover potential obstacles in a target road network. The framework has been evaluated in a real-world network of forest paths in the city of Cieza (Spain) showing quite promising results.

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.

Catacomb culture wagons of the Eurasian steppes

Antiquity ◽  
2014 ◽  
Vol 88 (340) ◽  
pp. 378-394 ◽  
Author(s):  
N.I. Shishlina ◽  
D.S. Kovalev ◽  
E.R. Ibragimova
Keyword(s):  
Stable Isotope ◽  
Isotope Analysis ◽  
Burial Mound ◽  
Careful Selection ◽  
Southern Russia ◽  
The Subject ◽  
The Individual ◽  
Wheeled Vehicles ◽  
Selection Of ◽  
Catacomb Culture

The origin and development of wheeled vehicles continues to fascinate today no less than when Stuart Piggott (1974) first wrote about the subject inAntiquity40 years ago. A growing number of examples from the steppes of southern Russia and Ukraine are providing new insights into the design and construction of these complex artefacts. A recent example from the Ulan IV burial mound illustrates the techniques employed and the mastery of materials, with careful selection of the kinds of wood used for the wheels, axles and other elements. Stable isotope analysis of the individual interred in this grave showed that he had travelled widely, emphasising the mobility of steppe populations.

scholarly journals Independent Map Enhancement for a Spatial Road Network: Fundamental Applications and Opportunities

2020 ◽  
Vol 10 (1) ◽  
pp. 8
Author(s):  
Sultan Alamri
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Road Construction ◽  
Peer To Peer ◽  
Transport Infrastructure ◽  
Traffic Density ◽  
Additional Time ◽  
Developing Cities ◽  
Time Required ◽  
Future Work

In many developing cities, the improvement of transport infrastructure is usually accompanied by major road construction and maintenance. This paper presents approaches and opportunities using peer-to-peer updating to improve spatial road networks undergoing construction and maintenance, which in turn will improve traffic flow and benefit cities overall. In many cities, the spatial road network requires maintenance, and these works often require traffic detours. With the current GPS (Global Positioning System) services, there is a noticeable delay in the updating of many spatial road networks. Thus, when a driver plans a trip to a certain location (such as Starbucks), his/her usual route may have changed, but the spatial road network in the GPS has not been updated. This can affect the user in many ways. For example, a trip that usually takes five minutes might now take half an hour, taking into account the additional time required to find alternative roads and possibly encountering more unexpected road closures, until the driver reaches his/her destination. This paper addresses this issue by proposing solutions that offer several advantages including a new peer-to-peer updating mechanism that helps to direct the driver to another route when road changes occur. Moreover, the peer-to-peer updating mechanism can enable the independent monitoring of road conditions and the updating of maps for newly-constructed roads, as well as the analysis of road congestions, traffic density, and people movements at certain times. Note that this work focuses on the conceptual ideas and approaches intended to improve independent maps, and the detailed algorithms have been left for future work.

Sign in / Sign up

Export Citation Format

Share Document