scholarly journals Learning to Generate Maps from Trajectories

2020 ◽  
Vol 34 (01) ◽  
pp. 890-897 ◽  
Author(s):  
Sijie Ruan ◽  
Cheng Long ◽  
Jie Bao ◽  
Chunyang Li ◽  
Zisheng Yu ◽  
...  
Keyword(s):  
Road Network ◽  
Traditional Approach ◽  
Trajectory Data ◽  
Embedded Devices ◽  
The Road ◽  
Mobile Objects ◽  
Map Generation ◽  
Spatial View ◽  
Topological Connectivity ◽  
Wide Usage

Accurate and updated road network data is vital in many urban applications, such as car-sharing, and logistics. The traditional approach to identifying the road network, i.e., field survey, requires a significant amount of time and effort. With the wide usage of GPS embedded devices, a huge amount of trajectory data has been generated by different types of mobile objects, which provides a new opportunity to extract the underlying road network. However, the existing trajectory-based map recovery approaches require many empirical parameters and do not utilize the prior knowledge in existing maps, which over-simplifies or over-complicates the reconstructed road network. To this end, we propose a deep learning-based map generation framework, i.e., DeepMG, which learns the structure of the existing road network to overcome the noisy GPS positions. More specifically, DeepMG extracts features from trajectories in both spatial view and transition view and uses a convolutional deep neural network T2RNet to infer road centerlines. After that, a trajectory-based post-processing algorithm is proposed to refine the topological connectivity of the recovered map. Extensive experiments on two real-world trajectory datasets confirm that DeepMG significantly outperforms the state-of-the-art methods.

scholarly journals An Automatic Method for Detection and Update of Additive Changes in Road Network with GPS Trajectory Data

2019 ◽  
Vol 8 (9) ◽  
pp. 411 ◽  
Author(s):  
Tang ◽  
Deng ◽  
Huang ◽  
Liu ◽  
Chen
Keyword(s):  
Road Network ◽  
Sampling Rate ◽  
Quality Data ◽  
Automatic Method ◽  
Trajectory Data ◽  
The Road ◽  
High Sampling Rate ◽  
Map Generation ◽  
Gps Trajectory Data ◽  
Gps Trajectory

Ubiquitous trajectory data provides new opportunities for production and update of the road network. A number of methods have been proposed for road network construction and update based on trajectory data. However, existing methods were mainly focused on reconstruction of the existing road network, and the update of newly added roads was not given much attention. Besides, most of existing methods were designed for high sampling rate trajectory data, while the commonly available GPS trajectory data are usually low-quality data with noise, low sampling rates, and uneven spatial distributions. In this paper, we present an automatic method for detection and update of newly added roads based on the common low-quality trajectory data. First, additive changes (i.e., newly added roads) are detected using a point-to-segment matching algorithm. Then, the geometric structures of new roads are constructed based on a newly developed decomposition-combination map generation algorithm. Finally, the detected new roads are refined and combined with the original road network. Seven trajectory data were used to test the proposed method. Experiments show that the proposed method can successfully detect the additive changes and generate a road network which updates efficiently.

scholarly journals A METHOD OF URBAN ROAD NETWORK EXTRACTION BASED ON FLOATING CAR TRAJECTORY DATA

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1579-1585
Author(s):  
C. Mi ◽  
F. Lu
Keyword(s):  
Road Network ◽  
Network Data ◽  
Trajectory Data ◽  
Network Information ◽  
Urban Road ◽  
The Road ◽  
Road Network Extraction ◽  
Geometric Precision ◽  
Road Width ◽  
Adaptive Radius

<p><strong>Abstract.</strong> With the gradual opening of floating car trajectory data, it is possible to extract road network information from it. Currently, most road network extraction algorithms use unified thresholds to ignore the density difference of trajectory data, and only consider the trajectory shape without considering the direction of the trajectory, which seriously affects the geometric precision and topological accuracy of their results. Therefore, an adaptive radius centroid drift clustering method is proposed in this paper, which can automatically adjust clustering parameters according to the track density and the road width, using trajectory direction to complete the topological connection of roads. The algorithm is verified by the floating car trajectory data of a day in Futian District, Shenzhen. The experimental results are qualitatively and quantitatively analyzed with ones of the other two methods. It indicates that the road network data extracted by this algorithm has a significant improvement in geometric precision and topological accuracy, and which is suitable for big data processing.</p>

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 Incremental Road Network Generation Based on Vehicle Trajectories

2018 ◽  
Vol 7 (10) ◽  
pp. 382 ◽  
Author(s):  
Zhongyi Ni ◽  
Lijun Xie ◽  
Tian Xie ◽  
Binhua Shi ◽  
Yao Zheng
Keyword(s):  
Real Time ◽  
Road Network ◽  
Trajectory Data ◽  
Network Generation ◽  
The Real ◽  
The Road ◽  
Vehicle Trajectories ◽  
Representation Point ◽  
Road Planning ◽  
Vehicle Trajectory

Nowadays, most vehicles are equipped with positioning devices such as GPS which can generate a tremendous amount of trajectory data and upload them to the server in real time. The trajectory data can reveal the shape and evolution of the road network and therefore has an important value for road planning, vehicle navigation, traffic analysis, and so on. In this paper, a road network generation method is proposed based on the incremental learning of vehicle trajectories. Firstly, the input vehicle trajectory data are cleaned by a preprocess module. Then, the original scattered positions are clustered and mapped to the representation points which stand for the feature points of the real roads. After that, the corresponding representation points are connected based on the original connection information of the trajectories. Finally, all representation points are connected by a Delaunay triangulation network and the real road segments are found by a shortest path searching approach between the connected representation point pairs. Experiments show that this method can build the road network from scratch and refine it with the input data continuously. Both the accuracy and timeliness of the extracted road network can continuously be improved with the growth of real-time trajectory data.

scholarly journals MAPPING AND CLASSIFICATION OF DIRECT EFFECTS OF THE FLOOD OF OCTOBER 2014 IN ATHENS

2017 ◽  
Vol 50 (2) ◽  
pp. 681 ◽  
Author(s):  
M. Diakakis ◽  
G. Deligiannakis ◽  
K. Katsetsiadou ◽  
E. Lekkas ◽  
M. Melaki ◽  
...  
Keyword(s):  
Road Network ◽  
Direct Effects ◽  
Severity Scale ◽  
The Road ◽  
Mobile Objects ◽  
Different Types ◽  
Flooded Area ◽  
The City ◽  
Sewerage Network

In 24 October 2014, a high intensity storm hit Athens’ western suburbs causing extensive flash flooding phenomena. The drainage and the sewerage network of the city were overwhelmed leading to catastrophic flood flows along the road network, flooding houses and businesses, sweeping away vehicles, injuring people and causing numerous problems in transportation across the city. Parts of the city were inundated for several hours, particularly in western Athens, namely Ilion, Menidi, Peristeri, Acharnai, Korydallos and Piraeus. This work examines and reconstructs in detail the flood's characteristics, the different types of direct effects within the urban environment and the severity of its direct impacts across Athens basin. Results show a concentration of flood damages in specific locations mostly along the city's natural drainage network or derelict streams and culverts. At their peak stage, floodwaters extended to an area of 4.9 square km recording a maximum depth of 170 cm in certain locations. Eight types of direct impacts were identified in 1223 impact locations, including effects on vegetation, geomorphology, erosion, mobile objects, buildings, infrastructure and human population. A severity scale was developed allowing effects to be divided in five severity classes across the flooded area and making possible the delineation of high impact sections of the city.

A Groundwork Based Novel Routing Protocol for Vehicular Ad hoc Networks

2017 ◽  
Vol 7 (11) ◽  
pp. 121
Author(s):  
Amolkirat Singh ◽  
Guneet Saini
Keyword(s):  
Routing Protocol ◽  
Packet Loss ◽  
Secure Communication ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Road Traffic ◽  
Traditional Approach ◽  
Unexpected Events ◽  
The Road ◽  
On The Road

Many people lose their life and/or are injured due to accidents or unexpected events taking place on road networks. Besides traffic jams, these accidents generate a tremendous waste of time and fuel. Undoubtedly, if the vehicles are provided with timely and dynamic information related to road traffic conditions, any unexpected events or accidents, the safety and efficiency of the transportation system with respect to time, distance, fuel consumption and environmentally destructive emissions can be improved. In the field of computer and information science, Vehicular Ad hoc Network (VANET) have recently emerged as an effective tool for improving road safety through propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. VANET is a research area which is in more demand among the researchers, the automobile industries and scientists to discover about the loopholes and advantages of the vehicular networks so that efficient routing algorithms can be developed which can provide reliable and secure communication among the mobile nodes.In this paper, we propose a Groundwork Based Ad hoc On Demand Distance Vector Routing Protocol (GAODV) focus on how the Road Side Units (RSU’s) utilized in the architecture plays an important role for making the communication reliable. In the interval of finding the suitable path from source to destination the packet loss may occur and the delay also is counted if the required packet does not reach the specified destination on time. So to overcome delay, packet loss and to increase throughput GAODV approach is followed. The performance parameters in the GAODV comes out to be much better than computed in the traditional approach.

ANALISIS PENGARUH PEMBANGUNAN JALAN LAYANG JANTI TERHADAP PERKEMBANGAN TATA RUANG KAWASAN JANTI STUDI KASUS : KAWASAN JANTI, DESA CATURTUNGGAL, KABUPATEN SLEMAN, D. I. YOGYAKARTA

2017 ◽  
Vol 11 (3) ◽  
pp. 255
Author(s):  
Jeky El Boru
Keyword(s):  
Road Network ◽  
Open Space ◽  
Qualitative Description ◽  
Analysis Method ◽  
Open Spaces ◽  
The Road ◽  
Before And After ◽  
Linkage Method ◽  
The Impact ◽  
Parking Place

Abstract: This research aims to analyze the impact of Janti Flyover Construction toward the growth of layout at Janti Urban Area, including structured space, open space, and linkage. Method used for data collecting are observation, air photograph monitoring, and interview, whereas the analysis method is qualitative description, which is the superimposed method of two layers, that are the layout condition before and after flyover construction. The result shows that the impact of Janti Flyover construction can be seen on building mass (solid), the increasing number of open spaces, including the road network, parking place, and park, whereas the relation between spaces, visually and structurally, can be seen on the growth of buildings which have new shapes and styles, therefore the performance of the overall building does not have a proportional shape. Considering Janti Street at the collective relation, its role is getting stronger as the main frame road network.Keywords: Flyover construction, layout changing, Janti AreaAbstrak: Penelitian ini bertujuan untuk menganalisis pengaruh pembangunan Jalan Layang Janti terhadap perkembangan tata ruang Kawasan Janti, meliputi ruang terbangun, ruang terbuka, serta hubungan antar ruang (“linkage”). Metode pengumpulan data dilakukan melalui observasi, pengamatan foto udara, dan wawancara; sedangkan metode analisis melalui deskripsi secara kualitatif yang berupa “superimposed method” dari dua lapisan kondisi lahan, yakni kondisi tata ruang sebelum dan sesudah pembangunan jalan layang. Hasil penelitian menunjukkan bahwa pengaruh pembangunan Jalan Layang Janti terdapat pada massa bangunan (“solid”), pertambahan ruang terbuka yang berupa jaringan jalan, parkir, dan taman; sedangkan pada hubungan antar ruang ̶ secara visual dan struktural ̶ yakni tumbuhnya bangunan dengan bentuk dan gaya baru, sehingga bentuk tampilan bangunan secara keseluruhan tidak proporsional. Pada hubungan kolektif, Jalan Janti semakin kuat perannya sebagai kerangka utama jaringan jalan.Kata kunci : Pembangunan jalan layang, tata ruang, Kawasan Janti

STUDY OF MOVEMENTS MOBILITY-IMPAIRED POPULATION GROUPS IN PEDESTRIAN ZONES OF THE STREET-ROAD NETWORK (in the example of city of Kiev)

2017 ◽  
Author(s):  
Oleksandra Cherednichenko ◽  
Keyword(s):  
European Union ◽  
Comparative Analysis ◽  
Road Network ◽  
Actual State ◽  
The European Union ◽  
Regulatory Requirements ◽  
Population Groups ◽  
The Road ◽  
Mobility Impaired

The results of the study of the main elements of unobstructed space are presented and the compliance of the actual state with the regulatory requirements of measures to ensure a safe, comfortable, accessible and informative pedestrian zone of the road network is analyzed. A comparative analysis of the main regulatory requirements for access ramps on the legislation of Ukraine and the European Union is carried out.

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