scholarly journals Discovering Congested Routes Using Vehicle Trajectories in Road Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Kyoung Soo Bok ◽  
He Li ◽  
Jong Tae Lim ◽  
Jae Soo Yoo

The popular route recommendation and traffic monitoring over the road networks have become important in the location-based services. The schemes to find out the congested routes were proposed by considering the number of vehicles in a road segment. However, the existing schemes do not consider the features of each road segment such as width, length, and direction in a road network. Furthermore, the existing schemes fail to consider the average moving speed of vehicles. Therefore, they can detect the incorrect density routes. To overcome such problems, we propose a new discovering scheme of congested routes through the analysis of vehicle trajectories in a road network. The proposed scheme divides each road into segments with different width and length in a road network. And then, the congested road segment is detected through the saturation degree of the road segment and the average moving speed of vehicles in the road segment. Finally, we compute the final congested routes by using a clustering scheme. The experimental results have shown that the proposed scheme can efficiently discover the congested routes in the different directions of the roads.

2019 ◽  
Vol 8 (9) ◽  
pp. 374 ◽  
Author(s):  
Li ◽  
Li ◽  
Li

Many studies have utilized global navigation satellite system (such as global positioning system (GPS)) trajectories in order to successfully infer road networks because such data can reveal the geometry and development of a road network, can be obtained in a timely manner, and updated on a low budget. Unfortunately, existing studies for inferring road networks from vehicle traces suffer from low accuracy, especially in dense urban regions and locations with complex structures, such as roundabouts, overpasses, and complex intersections. This study presents a novel two-stage approach for inferring road networks from trajectory points and capturing road geometry with better accuracy. First, a lane structure-aware filter is proposed to cluster vehicle trajectories influenced by high noise and outliers in order to reveal the continuous structure points of lane curves from massive trajectory points. Second, a road tracing operator is utilized to segment the road network geometry by inserting new vertices and segments to a vigorous vertex in the heading of the structure points that are extracted in the first step. Experimental results demonstrate the increased accuracy of the extracted roads and show that the proposed method exhibits strong robustness to noise and various sampling rates.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tinggui Chen ◽  
Shiwen Wu ◽  
Jianjun Yang ◽  
Guodong Cong ◽  
Gongfa Li

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.


2018 ◽  
Vol 7 (12) ◽  
pp. 472 ◽  
Author(s):  
Bo Wan ◽  
Lin Yang ◽  
Shunping Zhou ◽  
Run Wang ◽  
Dezhi Wang ◽  
...  

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.


2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
M. Marchetti ◽  
M. Moutton ◽  
S. Ludwig ◽  
L. Ibos ◽  
V. Feuillet ◽  
...  

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Minzhi Chen ◽  
Fan Wu ◽  
Min Yin ◽  
Jiangang Xu

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.


2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Tolesa Hundesa Muleta ◽  
Legesse Lemecha Obsu

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.


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Doohee Song ◽  
Kwangjin Park

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.


2018 ◽  
Vol 220 ◽  
pp. 10001
Author(s):  
Yu Lili ◽  
Zhang Lei ◽  
Su Xiaoguang ◽  
Li Jing ◽  
Zhang Xu ◽  
...  

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.


Algorithms ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 196
Author(s):  
Lars Gottesbüren ◽  
Michael Hamann ◽  
Tim Niklas Uhl ◽  
Dorothea Wagner

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.


Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1162
Author(s):  
Yang Zhang ◽  
Xiang Li ◽  
Qianyu Zhang

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.


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