scholarly journals A Model-Driven-to-Sample-Driven Method for Rural Road Extraction

2021 ◽  
Vol 13 (8) ◽  
pp. 1417
Author(s):  
Jiguang Dai ◽  
Rongchen Ma ◽  
Litao Gong ◽  
Zimo Shen ◽  
Jialin Wu
Keyword(s):  
Rural Areas ◽  
Template Matching ◽  
Color Space ◽  
Recall Rate ◽  
Road Extraction ◽  
Rural Roads ◽  
Model Driven ◽  
The Road ◽  
Center Point ◽  
Manual Input

Road extraction in rural areas is one of the most fundamental tasks in the practical application of remote sensing. In recent years, sample-driven methods have achieved state-of-the-art performance in road extraction tasks. However, sample-driven methods are prohibitively expensive and laborious, especially when dealing with rural roads with irregular curvature changes, narrow widths, and diverse materials. The template matching method can overcome these difficulties to some extent and achieve impressive road extraction results. This method also has the advantage of the vectorization of road extraction results, but the automation is limited. Straight line sequences can be substituted for curves, and the use of the color space can increase the recognition of roads and nonroads. A model-driven-to-sample-driven road extraction method for rural areas with a much higher degree of automation than existing template matching methods is proposed in this study. Without prior samples, on the basis of the geometric characteristics of narrow and long roads and using the advantages of straight lines instead of curved lines, the road center point extraction model is established through length constraints and gray mean contrast constraints of line sequences, and the extraction of some rural roads is completed through topological connection analysis. In addition, we take the extracted road center point and manual input data as local samples, use the improved line segment histogram to determine the local road direction, and use the panchromatic and hue, saturation, value (HSV) space interactive matching model as the matching measure to complete the road tracking extraction. Experimental results show that, for different types of data and scenarios on the premise, the accuracy and recall rate of the evaluation indicators reach more than 98%, and, compared with other methods, the automation of this algorithm has increased by more than 40%.

scholarly journals Lane-Level Road Extraction from High-Resolution Optical Satellite Images

2019 ◽  
Vol 11 (22) ◽  
pp. 2672
Author(s):  
Jiguang Dai ◽  
Tingting Zhu ◽  
Yilei Zhang ◽  
Rongchen Ma ◽  
Wantong Li
Keyword(s):  
High Resolution ◽  
Rural Areas ◽  
Template Matching ◽  
City Planning ◽  
Urban Expansion ◽  
Satellite Image ◽  
Road Extraction ◽  
Urban And Rural Areas ◽  
Optical Satellite Images ◽  
Vehicle Management

High-quality updates of road information play an important role in smart city planning, sustainable urban expansion, vehicle management, urban planning, traffic navigation, public health and other fields. However, due to interference from road geometry and texture noise, it is difficult to avoid the decline of automation while accurately extracting roads. Therefore, we propose a high-resolution optical satellite image lane-level road extraction method. First, from the perspective of template matching and considering road characteristics and relevant semantic relations, an adaptive correction model, an MLSOH (multi-scale line segment orientation histogram) descriptor, a sector descriptor, and a multiangle beamlet descriptor are proposed to solve the interference from geometry and texture noise in road template matching and tracking. Second, based on refined lane-level tracking, single-lane and double-lane road-tracking modes are designed to extract single-lane and double-lane roads, respectively. In this paper, Pleiades satellite and GF-2 images are selected to set up different scenarios for urban and rural areas. Experiments are carried out on the phenomena that restrict road extraction, such as tree occlusion, building shadow occlusion, road bending, and road boundary blurring. Compared with other methods, the proposed method not only ensures the accuracy of lane-level road extraction but also greatly improves the automation of road extraction.

scholarly journals Semi-Automatic Extraction of Rural Roads under the Constraint of Combined Geometric and Texture Features

2021 ◽  
Vol 10 (11) ◽  
pp. 754
Author(s):  
Hai Tan ◽  
Zimo Shen ◽  
Jiguang Dai
Keyword(s):  
Image Data ◽  
Texture Features ◽  
Remotely Sensed ◽  
Extraction Methods ◽  
Continuous Change ◽  
Road Extraction ◽  
Rural Roads ◽  
The Road ◽  
Road Width ◽  
Remotely Sensed Image

The extraction of road information from high-resolution remotely-sensed images has important application value in many fields. Rural roads have the characteristics of relatively narrow widths and diversified pavement materials; these characteristics can easily lead to problems involving the similarity of the road texture with the texture of surrounding objects and make it difficult to improve the automation of traditional high-precision road extraction methods. Based on this background, a semi-automatic rural road extraction method constrained by a combination of geometric and texture features is proposed in this paper. First, an adaptive road width extraction model is proposed to improve the accuracy of the initial road centre point. Then, aiming at the continuous change of curvature of rural roads, a tracking direction prediction model is proposed. Finally, a matching model under geometric texture constraints is proposed, which solves the problem of similarity between road and neighbourhood texture to a certain extent. The experimental results show that by selecting different types of experimental scenes or remotely sensed image data, compared with other methods, the proposed method can not only guarantee the road extraction accuracy but also improve the degree of automation to a certain extent.

scholarly journals Remote Sensing Road Extraction by Road Segmentation Network

2021 ◽  
Vol 11 (11) ◽  
pp. 5050
Author(s):  
Jiahai Tan ◽  
Ming Gao ◽  
Kai Yang ◽  
Tao Duan
Keyword(s):  
Remote Sensing ◽  
Attention Mechanism ◽  
Context Information ◽  
Road Extraction ◽  
Remote Sensing Images ◽  
Long Distance ◽  
The Road ◽  
Road Segmentation ◽  
Context Characteristics

Road extraction from remote sensing images has attracted much attention in geospatial applications. However, the existing methods do not accurately identify the connectivity of the road. The identification of the road pixels may be interfered with by the abundant ground such as buildings, trees, and shadows. The objective of this paper is to enhance context and strip features of the road by designing UNet-like architecture. The overall method first enhances the context characteristics in the segmentation step and then maintains the stripe characteristics in a refinement step. The segmentation step exploits an attention mechanism to enhance the context information between the adjacent layers. To obtain the strip features of the road, the refinement step introduces the strip pooling in a refinement network to restore the long distance dependent information of the road. Extensive comparative experiments demonstrate that the proposed method outperforms other methods, achieving an overall accuracy of 98.25% on the DeepGlobe dataset, and 97.68% on the Massachusetts dataset.

Modeling and Estimation of Headway Distributions

1997 ◽  
Vol 1591 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Serge P. Hoogendoorn ◽  
Hein Botma
Keyword(s):  
Estimation Method ◽  
Simulation Models ◽  
Independent Random Variables ◽  
Microscopic Simulation ◽  
Simple Analysis ◽  
Rural Roads ◽  
The Road ◽  
Road Capacity ◽  
Measurement Location ◽  
Fourier Series Analysis

A simple analysis to derive Branston’s generalized queueing model for (time-) headway distributions is presented. It is assumed that the total headway is the sum of two independent random variables: the empty zone and the free-flowing headway. The parameters of the model can be used to examine various characteristics of both the road (e.g., capacity) and driver-vehicle combinations (e.g., following behavior). Furthermore, the model can be applied to vehicle generation in microscopic simulation models and to safety analysis. To estimate the different parameters in the model, a new estimation method is proposed. This method, which was developed on the basis of Fourier-series analysis, was successfully applied to measurements collected on two-lane rural roads. The method was found to be both computationally less demanding and more robust than traditional parameter techniques procedures, such as maximum likelihood. In addition, the method provides more accurate results. Parameters in the model were examined with the developed estimation method. Estimates of these parameters at a specific period and a specific measurement location were to some extent transferable to other periods and locations. Application of the method to road capacity estimation is discussed.

Detour-Impact Index Method and Traffic Gathering Algorithm for Assessing Alternative Paths of Disrupted Roads

2021 ◽  
pp. 036119812110312
Author(s):  
Alessandro Pucci ◽  
Mario Lucio Puppio ◽  
Hélder Silva Sousa ◽  
Linda Giresini ◽  
José Campos Matos ◽  
...  
Keyword(s):  
Rural Areas ◽  
Traffic Data ◽  
Index Method ◽  
The Road ◽  
Data Collection Process ◽  
Impact Index ◽  
Before And After ◽  
Information User ◽  
Traffic Composition ◽  
Operative Costs

Infrastructure plays a key role in society. Recent collapses of bridges have underlined their importance for road functionality, causing disruptions to commuters and emergency vehicles. Major issues arise on rural roads, where the lack of redundancy leads to the isolation of entire communities. Actual approaches to assess the resilience of countryside roads rely on the availability of specific datasets, limiting their practical application; this issue is typically related to traffic data. This research aims to propose innovative algorithms to assess the road network’s vulnerability in rural areas, including a novel traffic data collection process and its calibration. The aggregate metric is called Detour-Impact Index (DII) and compares user costs before and after a disruptive event. The method uses traditional network-impact metrics in combination with a new algorithm that allows us to gather quantitative traffic data starting from qualitative information. User travel time showed good agreement between the proposed procedure and traditional web-based methods. Furthermore, the paper provides user delay costs functions accounting for traffic composition, trip purposes, vehicle operative costs, nonlinear volume–capacity relation, and average daily traffic. A significant aspect is the adaptability of this framework, as it is designed to be coupled with existing approaches. The method is demonstrated on a case study in Tuscany (Italy).

Scientific approach using AHP to prioritize low volume rural roads for pavement maintenance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Akhilesh Nautiyal ◽  
Sunil Sharma
Keyword(s):  
Rural Areas ◽  
Socioeconomic Development ◽  
Public Works ◽  
Relative Importance ◽  
Road Transportation ◽  
Rural Roads ◽  
Content Type ◽  
Pavement Maintenance ◽  
Low Volume ◽  
The Government

PurposeA large number of roads have been constructed in the rural areas of India to connect habitations with the nearest major roads. With time, the pavements of these roads have deteriorated and they need some kind of maintenance, although they all do not need maintenance at the same time, as they have all not deteriorated to the same level. Hence, they have to be prioritized for maintenance.Design/methodology/approachIn order to present a scientific methodology for prioritizing pavement maintenance, the factors affecting prioritization and the relative importance of each were identified through an expert survey. Analytic Hierarchy Process (AHP) was used to scientifically establish weight (importance) of each factor based on its relative importance over other factors. The proposed methodology was validated through a case study of 203 low volume rural roads in the state of Himachal Pradesh in India. Ranking of these roads in order of their priority for maintenance was presented as the final result.FindingsThe results show that pavement distresses, traffic volume, type of connectivity and the socioeconomic facilities located along a road are the four major factors to be considered in determining the priority of a road for maintenance.Research limitations/implicationsThe methodology provides a comprehensive, scientific and socially responsible pavement maintenance prioritization method which will automatically select roads for maintenance without any bias.Practical implicationsTimely maintenance of roads will also save budgetary expenditure of restoration/reconstruction, leading to enhancement of road service life. The government will not only save money but also provide timely benefit to the needy population.Social implicationsRoad transportation is the primary mode of inland transportation in rural areas. Timely maintenance of the pavements will be of great help to the socioeconomic development of rural areas.Originality/valueThe proposed methodology lays special emphasis on rural roads which are small in length, but large in number. Instead of random, a scientific method for selection of roads for maintenance will be of great help to the public works department for better management of rural road network.

Prediction of Design Hourly Volume on Rural Roads

2020 ◽  
pp. 036119812096556
Author(s):  
Miloš Petković ◽  
Vladan Tubić ◽  
Nemanja Stepanović
Keyword(s):  
Coefficient Of Determination ◽  
Rural Roads ◽  
The Road ◽  
Annual Average Daily Traffic ◽  
Proposed Model ◽  
Traffic Volumes ◽  
Implementation Costs ◽  
On The Road ◽  
Predicted Values ◽  
Design Hourly Volume

Design hourly volume (DHV) represents one of the most significant parameters in the procedures of developing and evaluating road designs. DHV values can be accurately and precisely calculated only on the road sections with the implemented automatic traffic counters (ATCs) which constantly monitor the traffic volume. Unfortunately, many road sections do not contain ATCs primarily because of the implementation costs. Consequently, for many years, the DHV values have been defined on the basis of occasional counting and the factors related to traffic flow variability over time. However, it has been determined that this approach has significant limitations and that the predicted values considerably deviate from the actual values. Therefore, the main objective of this paper is to develop a model which will enable DHV prediction on rural roads in cases of insufficient data. The suggested model is based on the correlation between DHVs and the parameters defining the characteristics of traffic flows, that is, the relationship between the traffic volumes on design working days and non-working days, and annual average daily traffic. The results of the conducted research indicate that the application of the proposed model enables the prediction of DHV values with a significant level of data accuracy and reliability. The coefficient of determination (R2) shows that more than 98% of the variance of the calculated DHVs was explained by the observed DHV values, while the mean error ranged from 4.86% to 7.84% depending on the number of hours for which DHV was predicted.

scholarly journals Speed Models for Motorcycle Riders for Two-lane Rural Roads

2021 ◽  
Vol 17 ◽  
pp. 595-603
Author(s):  
Panagiotis Lemonakis ◽  
George Botzoris ◽  
Athanasios Galanis ◽  
Nikolaos Eliou
Keyword(s):  
Prediction Models ◽  
Flow Speed ◽  
Operating Speed ◽  
Rural Roads ◽  
The Road ◽  
Horizontal Curves ◽  
Road Geometry ◽  
Speed Prediction ◽  
The Subject ◽  
On The Road

The development of operating speed models has been the subject of numerous research studies in the past. Most of them present models that aim to predict free-flow speed in conjunction with the road geometry at the curved road sections considering various geometric parameters e.g., radius, length, preceding tangent, deflection angle. The developed models seldomly take into account the operating speed profiles of motorcycle riders and hence no significant efforts have been put so far to associate the geometric characteristics of a road segment with the speed behavior of motorcycle riders. The dominance of 4-wheel vehicles on the road network led the researchers to focus explicitly on the development of speed prediction models for passenger cars, vans, pickups, and trucks. However, although the motorcycle fleet represents only a small proportion of the total traffic volume motorcycle riders are over-represented in traffic accidents especially those that occur on horizontal curves. Since operating speed has been thoroughly documented as the most significant precipitating factor of vehicular accidents, the study of motorcycle rider's speed behavior approaching horizontal curves is of paramount importance. The subject of the present paper is the development of speed prediction models for motorcycle riders traveling on two-lane rural roads. The model was the result of the execution of field measurements under naturalistic conditions with the use of an instrumented motorcycle conducted by experienced motorcycle riders under different lighting conditions. The implemented methodology to determine the most efficient model evaluates a series of road geometry parameters through a comprehensive literature review excluding those with an insignificant impact to the magnitude of the operating speeds in order to establish simple and handy models.

The Innovation of Natural Rubber Applied with Concrete Road Barriers in Thailand

2020 ◽  
Vol 103 ◽  
pp. 55-61
Author(s):  
Weeradej Cheewapattananuwong ◽  
Pathom Chaloeywares
Keyword(s):  
Natural Rubber ◽  
Best Practice ◽  
Natural Rubber Latex ◽  
Concrete Technology ◽  
Rural Roads ◽  
The Road ◽  
Crash Testing ◽  
Road Crash ◽  
Mitigation Methods ◽  
Strength And Durability

The Development of Natural Rubber for Traffic Devices in Thailand has been researched in several years. The enormous budgets have also been invested for the increasing of rubber prices. One of Traffic Devices is the application of natural rubber sheets for the protection of motorists - driving motorcycles as crashed through concrete barriers. The number of road side accidents on rural roads in Thailand is about 3 fatality per 10 kilometers. Therefore, the 11.20 MTB per a Fatality of accident cost is evaluated to be 3,360 TB per km. This leads to the mitigation methods to remedy a symptom’s motorist from severity to moderate and mild respectively. The solution is to find the best practice of road barrier which is applied with natural rubber latex glued with concrete barrier. In addition, the composite materials will be calculated of the modulus of elasticity and properties such as, strength and durability. The simulation of crashes, finite element of materials, LRFD and Concrete Technology methods will be taken into consideration. The testing of material in Thailand will be firstly applied for these, for example the road crash testing under the standard of NCHRP – TL3 (100 kph) will be taken into account.

Sign in / Sign up

Export Citation Format

Share Document