scholarly journals Graphic Simplification and Intelligent Adjustment Methods of Road Networks for Navigation with Reduced Precision

2020 ◽  
Vol 9 (8) ◽  
pp. 490
Author(s):  
Qingsheng Guo ◽  
Huihui Wang ◽  
Jie He ◽  
Chuanqi Zhou ◽  
Yang Liu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
High Precision ◽  
Road Network ◽  
Rapid Development ◽  
Road Networks ◽  
Semantic Features ◽  
The Road ◽  
Topological Relationships ◽  
Elite Strategy ◽  
Navigation Software

With the rapid development of high-precision road network maps, low-precision road network maps (basic data unrelated to hardware) will need to be directly produced for traditional navigation software from high-precision maps. To do so, large amounts of vector data representing road networks must be simplified and spatial directional similarity in road networks must be maintained while reducing precision. In this study, an elite strategy genetic algorithm based on the grid model is applied to spatial directional adjustment in road networks for producing road network maps for traditional navigation. Firstly, semantic features and critical vertices are extracted from the road network with high precision. Secondly, some high-precision vertices are eliminated under constraints of the digital navigation map. During this process, the local shape maintenance of the road is considered, and the destruction of the spatial topological relationships is avoided. Thirdly, a genetic algorithm for minimizing the total changes in road azimuths at nodes of road networks is developed to maintain spatial directional relationships while reducing precision. Experimental results and visualization effects on the test data of different cities show that this method is suitable for generating road network maps for traditional navigation software from high-precision ones.

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.

scholarly journals An Intersection-First Approach for Road Network Generation from Crowd-Sourced Vehicle Trajectories

2019 ◽  
Vol 8 (11) ◽  
pp. 473 ◽  
Author(s):  
Caili Zhang ◽  
Longgang Xiang ◽  
Siyu Li ◽  
Dehao Wang
Keyword(s):  
Road Network ◽  
Rapid Development ◽  
Road Networks ◽  
Uneven Distribution ◽  
Trajectory Data ◽  
Network Generation ◽  
The Road ◽  
Lower Accuracy ◽  
Road Intersections ◽  
Vehicle Trajectory

Extracting highly detailed and accurate road network information from crowd-sourced vehicle trajectory data, which has the advantages of being low cost and able to update fast, is a hot topic. With the rapid development of wireless transmission technology, spatial positioning technology, and the improvement of software and hardware computing ability, more and more researchers are focusing on the analysis of Global Positioning System (GPS) trajectories and the extraction of road information. Road intersections are an important component of roads, as they play a significant role in navigation and urban planning. Even though there have been many studies on this subject, it remains challenging to determine road intersections, especially for crowd-sourced vehicle trajectory data with lower accuracy, lower sampling frequency, and uneven distribution. Therefore, we provided a new intersection-first approach for road network generation based on low-frequency taxi trajectories. Firstly, road intersections from vector space and raster space were extracted respectively via using different methods; then, we presented an integrated identification strategy to fuse the intersection extraction results from different schemes to overcome the sparseness of vehicle trajectory sampling and its uneven distribution; finally, we adjusted road information, repaired fractured segments, and extracted the single/double direction information and the turning relationships of the road network based on the intersection results, to guarantee precise geometry and correct topology for the road networks. Compared with other methods, this method shows better results, both in terms of their visual inspections and quantitative comparisons. This approach can solve the problems mentioned above and ensure the integrity and accuracy of road intersections and road networks. Therefore, the proposed method provides a promising solution for enriching and updating navigable road networks and can be applied in intelligent transportation systems.

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 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.

scholarly journals Impact of Road Network Topology on Public Transportation Development

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.

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 A Privacy-Preserving Location-Based System for Continuous Spatial Queries

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Doohee Song ◽  
Kwangjin Park
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Nearest Neighbors ◽  
Privacy Preserving ◽  
Spatial Queries ◽  
The Road ◽  
Mobile Clients ◽  
Previous Location

K-anonymization generated a cloaked region (CR) that was K-anonymous; that is, the query issuer was indistinguishable from K-1 other users (nearest neighbors) within the CR. This reduced the probability of the query issuer’s location being exposed to untrusted parties (1/K). However, location cloaking is vulnerable to query tracking attacks, wherein the adversary can infer the query issuer by comparing the two regions in continuous LBS queries. This paper proposes a novel location cloaking method to resist this attack. The target systems of the proposed method are road networks where the mobile clients’ trajectories are fixed (the road network is preknown and fixed, instead of the trajectories), such as subways, railways, and highways. The proposed method, called adaptive-fixed K-anonymization (A-KF), takes this issue into account and generates smaller CRs without compromising the privacy of the query issuer’s location. Our results show that the proposed A-KF method outperforms previous location cloaking methods.

scholarly journals Continuous Anonymity with Users in the Same Direction in Road Networks

2018 ◽  
Vol 220 ◽  
pp. 10001
Author(s):  
Yu Lili ◽  
Zhang Lei ◽  
Su Xiaoguang ◽  
Li Jing ◽  
Zhang Xu ◽  
...  
Keyword(s):  
Euclidean Space ◽  
Privacy Protection ◽  
Road Network ◽  
Location Privacy ◽  
Road Networks ◽  
The Road ◽  
Shortest Distance ◽  
Location Privacy Protection ◽  
Road Segments

Compared with the Euclidean space, road network is restricted by its direction in traveling, velocity and some other attribute profiles. So the algorithms that designed for the Euclidean space are usually invalid and difficult to provide privacy protection services. In order to cope with this problem, we have proposed an algorithm to provide the service of collecting anonymous users that their directions in traveling similar with the initiator in the road networks. In this algorithm, the shortest distance between multiple road segments is calculated, and then utilizes the distance to select the user who has the same direction in traveling with the initiator. Consequently, the problem of the discrepancy of the anonymous users in the routing that invalidates the location privacy protection is solved. At last, we had compared this algorithm with other similar algorithms, and through the results of the comparison and the cause of this phenomenon, we have concluded that this algorithm is better not only in the level of privacy protection, but in the performance of execution efficiency.

scholarly journals Faster and Better Nested Dissection Orders for Customizable Contraction Hierarchies

Algorithms ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 196
Author(s):  
Lars Gottesbüren ◽  
Michael Hamann ◽  
Tim Niklas Uhl ◽  
Dorothea Wagner
Keyword(s):  
Shared Memory ◽  
Graph Partitioning ◽  
Road Network ◽  
Road Networks ◽  
Geographical Information ◽  
Nested Dissection ◽  
High Quality ◽  
The Road ◽  
Inertial Flow ◽  
Path Queries

Graph partitioning has many applications. We consider the acceleration of shortest path queries in road networks using Customizable Contraction Hierarchies (CCH). It is based on computing a nested dissection order by recursively dividing the road network into parts. Recently, with FlowCutter and Inertial Flow, two flow-based graph bipartitioning algorithms have been proposed for road networks. While FlowCutter achieves high-quality results and thus fast query times, it is rather slow. Inertial Flow is particularly fast due to the use of geographical information while still achieving decent query times. We combine the techniques of both algorithms to achieve more than six times faster preprocessing times than FlowCutter and even faster queries on the Europe road network. We show that, using 16 cores of a shared-memory machine, this preprocessing needs four minutes.

Sign in / Sign up

Export Citation Format

Share Document