Road Orientation Research Articles

Modelling of rock slope failures due to geological discontinuties to minimize risk from road cut failures

Rock slope failures are common issues on road cuts. Geological discontinuities are one of main causal factors for the occurrence of rock slope failures and most rocks exposed in road cuts show slope failures as rock falls. Most of the roads constructed across hilly areas have risk from such slope failures resulting in adverse effects on road uses. The aim of the present study is to model rock slope failures which can be used at the design stage to reduce the risk from structural geological features especially planer structures (foliation and joint planes). Two road traces which run across Sri Lankan mountain terrains (Avissawella – Hatton and Balangoda – Haputale roads) were used for the study. Field data on orientation of structural geological features and the type of rock involved in rock falls were collected from 44 locations along both road stretches. Dip Anlysist 2.0 was used for modelling the slope failures. Wedge failure, Toppling and Plane failure modes were considered. Wedge failure is the most common rock slope failure observed. When compared with field observations, the model shows 64% precision from 44 locations studied. The model revealed that the risk from road cut failures can be minimized by optimising existing road orientation and slope angle of the cut. The slope failures can be reduced by using this type of model analysis during the design stage of new roads.

Analysis of urban ventilation potential using rule-based modeling

Successful and efficient urban planning requires direct, rapid evaluations of the urban ventilation potential. An urban ventilation environment can be analyzed and evaluated using numerical simulations; however, such simulations require considerable time and effort, especially at the start of planning or when the area is vast. This study presents a method that can rapidly analyze urban ventilation potential of the whole city and each district by combining the rule-based modeling method with urban enclosure index. The first step of the proposed method is to rapidly generate building models using rule-based modeling, and the buildings in different districts are color coded by their use. Then, several vertical sections of the whole city and each district are cut, and the sectional data is extracted for plotting the enclosure charts. Finally, the enclosure index charts are superimposed on the urban wind rose diagram to analyze the ventilation potential of the whole city and each district, and optimization suggestions are proposed based on the analysis results. A case study was then performed on Lipu County, Guangxi, China and the optimization suggestions were proposed from the aspects of road orientations, building layout and the arrangement of greenbelts and open recreational space.

An Enhanced Viola-Jones Vehicle Detection Method From Unmanned Aerial Vehicles Imagery

This research develops an advanced vehicle detection method, which improves the original Viola-Jones (V-J) object detection scheme for better vehicle detections from low-altitude unmanned aerial vehicle (UAV) imagery. The original V-J method is sensitive to objects’ in-plane rotation, and therefore has difficulties in detecting vehicles with unknown orientations in UAV images. To address this issue, this research proposes a road orientation adjustment method, which rotates each UAV image once so that the roads and on-road vehicles on rotated images will be aligned with the horizontal direction and the V-J vehicle detector. Then, the original V-J can be directly applied to achieve better efficiency and accuracy. The enhanced V-J method is further applied for vehicle tracking. Testing results show that both vehicle detection and tracking methods are competitive compared with other existing methods. Future research will focus on expanding the current methods to detect other transport modes, such as buses, trucks, motorcycles, bicycles, and pedestrians.

Fast lane detection based on bird’s eye view and improved random sample consensus algorithm

In order to ensure the safety of drivers, Advanced Driving Assistance System (ADAS) has drawn more and more attention. The Lane Departure Warning system is one of the most important parts of ADAS. However, fast and stable lane marking detection is the precondition of it under complex background. In this paper, we proposed a new lane detection method through bird's eye view and improved RANSAC (Random Sample Consensus) algorithm based on the inspiration that extraction of road features from remote sensed images. According to the bird's eye view of the road image, we can recognize the line marking through Progressive Probabilistic Hough transform instead of lane detection. Then, the detected lines are grouped by a new distance-based weighting scheme and we can get the fields of candidate lanes. For each of the fields, lanes are refined through improved RANSAC algorithm and fitted by double models. Hence, the road orientation can be predicted by the curvature and straight line's slope. At last, our experimental results indicated that the lane detection algorithm has good robustness and real-time under various road environment.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Analyzing the landscape characteristics promoting the establishment and spread of gorse (Ulex europaeus) along roadsides

AbstractThe International Union for Conservation of Nature listed gorse (Ulex europaeus, Fabaceae), a heliophilous evergreen shrub, as one of the world's 100 worst invasive species. Over the years, multiple attempts have been made for controlling gorse, including biological methods, but they have not been fully successful. This study aims to investigate some aspects that still remain unexplored such as the relationship between anthropogenic disturbances with the spatial mechanisms of species spread. We aimed to fill this gap by analyzing the role of transportation network configurations and landscape context on gorse propagation. We surveyed the presence of gorse in southern Brazilian forest‐grassland mosaics by completing landscape‐level road transects coupled with remote sensing, to evaluate land use and landscape structure. A binary logistic regression model was performed to test the influence of independent variables (e.g., road orientation, type and category in addition to distance to the nearest habitat patch of forest, grassland and anthropogenic area) on gorse occurrence. Our results showed that the structure of road networks can facilitate the spread of heliophilous taxa like gorse. Specifically, local, paved, NWSE and NS‐oriented (which exhibited high light exposure) roads had the highest probability of finding gorse. This suggests that human transportation activity (traffic, road construction, and maintenance) constitutes a significant dispersal agent for the species. In addition, the landscape matrix context also played a significant role; gorse was most prevalent along roadsides close to urban or agricultural areas than to forests and grasslands. No area was completely free from disturbances, such as fire, livestock grazing, and silviculture, in these seminatural landscapes. We concluded that, disturbances affecting small‐scale processes, at roadside and adjacent habitat patches, were probably as important factors explaining gorse occurrence as the urban impact. Furthermore, the current work also emphasizes the need of understanding the complexity of interacting factors. Our work has important implications for ecosystem conservation and habitat management, and consequently should be considered a prior step in establishing new approaches for gorse control.

Semi Deterministic Hybrid Model for Path Loss Prediction Improvement

Mobile radio path loss modeling is an important aspect of network planning which ensures an improved quality of service to the subscribers. In this paper, the predictions made by COST 231 Walfisch-Ikegami propagation model to estimate the path loss of the mobile signals are improved by proposing a hybrid model. The modified model combines the deterministic aspects of ray tracing along with statistical processing of the empirical measurements. It includes a loss term computed for multiple reflections by using the method of images. The ten ray urban street canyon model is extended to compute reflections from multiple paths. The deterministic approach is merged with the statistical variations in the original Walfisch-Ikegami model. It consists of modeling the multi screen diffraction loss, roof to street loss and street orientation function by considering the height of the buildings, the separation and the road orientation angle as random variables with Gaussian distribution. The proposed hybrid model is validated by measurements of GSM 900MHz signals collected in Hyderabad city of Southern India. The performance of the proposed model is evaluated in terms of Prediction Error, Root Mean Square Error and other metrics. The results justify the improvement in the path loss prediction of the proposed semi deterministic hybrid model. This could be useful in link budget analysis and deployment of future cellular networks for the specified urban region and similar scenarios.

Effects of Orientation of Urban Roads on the Local Thermal Environment in Guangzhou City

The continuous Guangzhou expansion leads to more and more construction of the city road, which is a special underlying surface. In 2012, the total length of the road in Guangzhou is 9050.715km. Among them, the total length of the highway is 652.6km and the remaining 6044km is urban roads. There are 47 main roads with a distance of 5685km and area of 3953.63 million square meters.The roads are commonly constructed by asphalt and cement concrete whose heat absorption rate is higher than that of the green land and water body, while the thermal capacity of the asphalt and cement concrete is smaller than that of the green land and water body. This means that the roads with asphalt and cement concrete can absorb the solar radiation largely and cause the big temperature increase itself, which will increase the summer energy consumption of vehicles on the road and affect the outdoor thermal comfort of pedestrians. Nowadays, the construction of roads has become one of the main-reasons for urban heat island.In another hand, road provides the broad path for urban ventilation, which makes it become an important element for the construction of urban wind corridor. According to above negative impact on urban heat island and positive impact on urban ventilation, great difficulties still remain when urban planners attempt to design the urban roads to realize the comfortable outdoor thermal environment.The orientation of urban roads is an important element for the road design. Its relationship with the prevailing wind direction can somehow affect the city temperature distribution and ventilation efficiency. Fazia Ali-Toudert from University of Freiburg concludes that in urban street the roads with east-west orientation are less efficient in releasing heat compared with the north-south orientation (Fazia Ali-Toudert, 2006). Andreou concludes that, under the same condition of shade and solar energy, street geometry, height/width ratio, orientation and trees can affect urban canyon microclimate (Fazia Ali-Toudert, 2014). They do not have a detailed study of the relationship between the orientation towards the prevailing wind, as well as to the impact on the surrounding thermal environmentThis paper uses the method of numerical simulation to analyze the impact of road orientation on the thermal environment of Guangzhou Zhujiang New Town. Some implications for the urban road design are obtained. Orientation of the road has a great influence on the local thermal environment for example in windless area or with respect to high-rise buildings in low-lying areas.

Vehicles overtaking detection using RGB-D data

Outstanding breakthrough in traffic video surveillance has been made with the development of computer vision techniques. However, there are still some problems to be solved due to the limitations of two-dimensional (2D) video data. With the popularity of three-dimensional (3D) cameras, high-quality color and depth data can be obtained simultaneously in real time through the video stream. In this paper, we propose a vehicles overtaking detection method using RGB-D data captured by the Kinect device in simulated traffic scenes. Vehicles are detected and tracked with a robust traffic scene understanding on RGB-D data. The depth data is utilized to recognize vehicles overtaking by analyzing the posture change of vehicles in different scenes. The principle of vehicles overtaking detection is to fit the line of vehicle side in the coordinate system and calculate the angle between the vehicle side and the road orientation. As a consequence, the posture change of the vehicle can be recognized. The proposed method is evaluated using simulation experiments which show that our work has good performance in vehicles overtaking detection and tracking.

Study on the appropriate selection of urban heat island measure technologies to urban block properties

Abstract In this study, we analyzed the effects of introducing urban heat island measure technologies in a typical street canyon model to aid the selection of a suitable technology. It is appropriate to use street trees for improving the thermal environment of a sidewalk and high reflectance paint or water-retentive pavement for the reduction of surface temperature on the roadway. Reduction of solar radiation gain to the sidewalk pavement surface depends on the location and area of the street tree shadows, which are likely to occur on the northern sidewalk of an east–west road rather than an eastern (or a western) sidewalk of a north–south road. Moreover, the area of the shadow is proportional to the square of the width of tree crown (the radius) and inversely proportional to the distance between trees. Thus, it is necessary to prioritize these considerations based on the road orientation and time when the pedestrian use of sidewalk is the highest.

Exploring the processes governing roadside pollutant concentrations in urban street canyon

This paper describes an in-depth analysis to investigate the huge variation in the measured roadside air-pollutant concentrations of carbon monoxide and nitrogen dioxide in terms of the traffic flow levels, the orientation of the street to the prevailing wind, the wind speed, temperature and barometric pressure. The work has attempted to develop generic parameters that can be applied to other urban areas. However, in the absence of a measure of congestion at the site in Palermo (Italy), the methodological approach proposed used the simultaneous noise measurements, in units of decibels (B), to help parameterise a generic congestion indicator in terms of the traffic flow. The potential transferability of the approach was demonstrated for a site in Marylebone Road, London (UK), given the similarity of the two study sites, canyon shape, traffic characteristics and road orientation. The results showed that, within the range of data available, noise levels could be used as a proxy for flow change on the shoulders of the peak hour and hence congestion and a generic relationship with factors statistically significant at 99% confidence allows roadside concentrations due to traffic to be estimated with a regression coefficient of R(2) = 0.73 (R = 0.85). The research demonstrates that whilst there are indeed underlying relationships that can explain the roadside concentrations based on traffic and meteorological conditions, evidence is presented that confirms the complexity of the physical and chemical processes that govern roadside concentrations.

街路形態に応じたヒートアイランド対策技術の適材適所の導入検討に関する研究

Abstract In this study, we analyzed the effects of introducing urban heat island measure technologies in a typical street canyon model to aid the selection of a suitable technology. It is appropriate to use street trees for improving the thermal environment of a sidewalk and high reflectance paint or water-retentive pavement for the reduction of surface temperature on the roadway. Reduction of solar radiation gain to the sidewalk pavement surface depends on the location and area of the street tree shadows, which are likely to occur on the northern sidewalk of an east–west road rather than an eastern (or a western) sidewalk of a north–south road. Moreover, the area of the shadow is proportional to the square of the width of tree crown (the radius) and inversely proportional to the distance between trees. Thus, it is necessary to prioritize these considerations based on the road orientation and time when the pedestrian use of sidewalk is the highest.

Field Measurement and Analysis of the Micro Climate of a Campus Square

A square is an important multi-functional public space on campus, which can be used as a venue for traffic, gathering, recreational activities and cultural events, and thus the thermal environment of the campus square will directly influence the overall environmental quality of campus. This paper studies a campus square in the summer-hot and winter-cold region, selects typical positions to conduct actual measurement of parameters, such as temperature, relative humidity, wind speed and solar radiation, which indicate the thermal environment. Based on data collection and analysis, it is concluded that the thermal environment of the campus square is affected by microclimate factors such as the square underlying surface properties, vegetation and building and road orientations. This paper is aimed at exploring the regularity of the correlation between microclimate factors and thermal environment in order to facilitate the improvement of the thermal environment of the campus square, make it more comfortable and provide ideas for the landscape and architectural environment design.

Field strength prediction of mobile communication network based on GIS

This article describes GIS-based models successfully developed for predicting the coverage of Cityphone cellular network, visualizing the predicted signal strength, and analyzing the field strength coverage. In order to predict the signal coverage strength of communication network more accurately, the spatial and nonspatial databases of a mobile cellular network are combined by GIS and produce the necessary parameters. A GIS model named COST-231-Walfisch–Ikegami model (WIM) is developed for signal coverage prediction in Ho Chi Minh City. Radio-line-of-sight and nonradio-line-of-sight conditions can be determined by this model. In addition, in case of nonradio-line-of-sight conditions, average building height, building separation, building width, incident radio path, and road orientation with respect to the direct radio path were obtained using GIS. Road orientation loss, multiscreen diffraction loss, and shadowing gain were predicted more accurate by this model. The scale of maps in the experiment was 1:2000 and the average of floor height was 3 m because there were no exact building height measurements. Statistical results show that the path loss predicted by the COST 231 WIM overcame the real path loss of each cell station. And this method can be used for signal coverage prediction of mobile cellular network in urban areas. Compared to the current situation with the Ho Chi Minh City Posts and Telecommunications system, this model can be effectively applied to improve the Cityphone mobile network quality as well as capability. Developed GIS models can help designers in predicting cell station coverage using real spatial maps that make the results more reliable. This research can help network operators improve the network quality and capability with the best investment efficiently.

Local and regional sources of C2–C8 hydrocarbon concentrations at a sub-urban motorway site (M4) in Ireland

Approximately 8 months of C(2)-C(8) online-sampling of hydrocarbons was carried out in the vicinity of a sub-urban Motorway in Ireland. A comprehensive description of air quality monitoring adjacent to the M4 at Leixlip in Ireland is presented where the primary objective was to ascertain the local and regional C(2)-C(8) hydrocarbon emissions in the vicinity of a sub-urban Motorway (M4). Nineteen HC compounds were monitored where different analysis techniques were employed in an attempt to isolate the Motorway source effect. Included in these were analyses into various hydrocarbon ratios, including 1,3 butadiene/propene, m + p xylene/ethylbenzene and ethene/acetylene. In addition, the local source effect was quantitatively assessed using COPERTIII and CALINE4 modelling, and the regional effects and source contributions were analysed using 2-D back trajectory analysis. Our results show that conditions associated with high regional contributions are associated with conditions also conducive to high local contributions, particularly evident at the M4 site due to the road orientation, as air masses from continental Europe and the UK are likely to be associated with near parallel, slow moving local winds relative to the M4, yielding higher local contributions.

Automatic and Accurate Extraction of Road Intersections from Raster Maps

Since maps are widely available for many areas around the globe, they provide a valuable resource to help understand other geospatial sources such as to identify roads or to annotate buildings in imagery. To utilize the maps for understanding other geospatial sources, one of the most valuable types of information we need from the map is the road network, because the roads are common features used across different geospatial data sets. Specifically, the set of road intersections of the map provides key information about the road network, which includes the location of the road junctions, the number of roads that meet at the intersections (i.e., connectivity), and the orientations of these roads. The set of road intersections helps to identify roads on imagery by serving as initial seed templates to locate road pixels. Moreover, a conflation system can use the road intersections as reference features (i.e., control point set) to align the map with other geospatial sources, such as aerial imagery or vector data. In this paper, we present a framework for automatically and accurately extracting road intersections from raster maps. Identifying the road intersections is difficult because raster maps typically contain much information such as roads, symbols, characters, or even contour lines. We combine a variety of image processing and graphics recognition methods to automatically separate roads from the raster map and then extract the road intersections. The extracted information includes a set of road intersection positions, the road connectivity, and road orientations. For the problem of road intersection extraction, our approach achieves over 95% precision (correctness) with over 75% recall (completeness) on average on a set of 70 raster maps from a variety of sources.

Tracking Road Centerlines from High Resolution Remote Sensing Images by Least Squares Correlation Matching

This paper describes a semi-automatic algorithm for tracking road centerlines from satellite images at 1 m resolution. We assume that road centerlines are visible in the image and that among points on road centerlines similarity transformation holds. Previous approaches proposed for semi-automatic road extraction include energy minimization and template matching with global enforcement. In this paper we will show that least squares correlation matching alone can work for tracking road centerlines. Our algorithm works by defining a template around a user-given input point, which shall lie on a road centerline, and then by matching the template against the image along the orientation of the road under consideration. Once matching succeeds, new match proceeds by shifting a matched target window further along road orientation. By repeating the process above, we obtain a series of points, which lie on a road centerline successively. An Ikonos image over Seoul area was used for test. The algorithm could successfully extract road centerlines once valid input points were provided from a user. The contribution of this paper is that we proved template matching could offer wider applicability in feature extraction, and we designed a new template matching scheme that worked for feature extraction without global enforcements.

Screening and Scenarios of Traffic Emissions at Trier, Germany

In the course of the European Council Directive on permissible air pollutant limit values, valid starting from 2005 there is an urgent call for action, particularly for fine dust (PM10). Current investigations (Junk & Helbig 2003, Reuter & Baumüller 2003) show that the limit values in certain places in congested areas are exceeded. Only if it is possible to locate these Hot Spots purposeful measures to reduce the ambient air pollution can be conducted. For an efficient identification of these Hot Spots numerical computer models or establishing special measurements networks are too expensive. Using the statistical model STREET 5.0 (KTT 2003) a cost-effective screening of the air pollution situation caused by the traffic can be done. STREET is based on the 3-dimensional micro-scale non-hydrostatic flow- and dispersion model MISCAM (Eichhorn 1989). The results of over 100.000 different calculations with MISCAM are stored in a Database and used to calculate the emissions with STREET. In collaboration with the city council of Trier more than 150 streets were investigated, mapped, and calculated. A special urban climate measuring network supplies the necessary meteorological input data about the wind field and precipitation events in the valley of the Moselle. Information about road width and road orientation as well as building density was derived from aerial photographs. Traffic censuses and mobile air pollutants measurements supplied the remaining input data. We calculated the mean annual air pollutant concentrations for NO2, CO, SO2, O3, benzene as well as PM10. A comparison of the model results with the values obtained from the stations of the central emission measuring network of Rhineland-Palatinate (ZIMEN, annual report 2002) shows very good agreements. The model was not only used to calculate the annual air pollutant but also for urban planning and management. The absolute level of the air pollutant is mainly dependent on the amount of traffic in the street canyons. Therefore four different case-scenarios with varying quantity of traffic were calculated and interpreted for each street. The results of the calculation show that on the basis of the mean values for both NO2 and benzene, it is not to be expected that the limits Furthermore the model can be used to find the maximum tolerable numbers of cars for a street without exceeding the air pollutant thresholds.

A Study on the Road Network Characteristics of Spanish Cities

The aim of this paper is to study the characteristics of road network in Spanish historical cities. We measured road length, road orientation, and intersection numbers of Spanish cities and historical cities in other countries. Using the principal component analysis and the cluster analysis, Spanish cities are mainly classified into 3 types; 1) southern old cities whose road networks are of labyrinthian type, 2) northern old cities whose road networks are similar to European medieval cities, 3) modern cities developed in the turn of 20 th century which have rectilinear road networks around the old city center.

Land mobile satelliteKa-band shadowing statistics in built-up areas for different road orientations

There is a growing interest in land mobile satellite systems at Ka-band for broadband communications. An accurate characterization of shadowing effects is needed to help plan such new systems. Here, the analysis of a measurement campaign carried out in urban and suburban areas in which shadowing effects were recorded is presented. © 1998 John Wiley & Sons, Inc. Microwave Opt Technol Lett 19: 381–384, 1998.