Road Elements Research Articles

A Representation Method for Complex Road Networks in Virtual Geographic Environments

Road networks are important for modelling the urban geographic environment. It is necessary to determine the spatial relationships of road intersections when using maps to help researchers conduct virtual urban geographic experiments (because a road intersection might occur as a connected cross or as an unconnected bridge overpass). Based on the concept of using different map layers to organize the render order of each road segment, three methods (manual, semi-automatic and mask-based automatic) are available to help map designers arrange the rendering order. However, significant efforts are still needed, and rendering efficiency remains problematic with these methods. This paper considers the Discrete, Crossing, Overpass, Underpass, Conjunction, Up-overlap and Down-overlap spatial relationships of road intersections. An automatic method is proposed to represent these spatial relationships when drawing road networks on a map. The data-layer organization method (reflecting road grade and elevation-level information) and the symbol-layer decomposition method (reflecting road covering order in the vertical direction) are designed to determine the rendering order of each road element when rendering a map. In addition, an “auxiliary-drawing-action” (for drawing road segments belonging to different grades and elevations) is proposed to adjust the rendering sequences automatically. Two experiments are conducted to demonstrate the feasibility and efficiency of the method, and the results demonstrate that it can effectively handle spatial relationships of road networks in map representations. Using the proposed method, the difficulty of rendering complex road networks can be reduced.

DEVELOPMENT OF CARGO TRANSPORTATION SYSTEM BY ROAD ON THE BASIS OF LOGISTICS PRINCIPLES

Рurpose. The article is aimed to develop and adapt the theoretical and methodological foundations for improving logistics system of cargo delivery by road transport in the framework of the scientific support of formation processes of transport-logistical system of the country. Methodology. The theory of system functioning control requires formalization of connections within the system. The qualitative and quantitative characteristics of entity were performed and the regularities of elements interaction in the system of road goods transportation were found out. The role of the road in transport industry and the influence of transportation and logistics space on the road itself in the process of its functioning were clarified. In the study of this topic the system approach, methods of synthesis and rational problem solving, theory of mass service were used. Findings. The work presents the highway as an element of the cargo transportation system that will make it possible to increase its economic efficiency in a constantly changing environment of transportation and logistics space according to the chosen criterion, the lower total costs to promote material flow. Theoretical-methodological bases of perfection of logistics system of cargo delivery by road transport include substantiation for the use of logistics as an effective control element to reduce the costs associated with goods transportation. They are distinguished by the presence of evidence-based methods for calculating the timing and sequence of execution of road works, logistic integration involved in the carriage of goods of the enterprises, structure and volume of material and accompanying flows and the formation of the logistics chain of its promotion. Originality. The road is represented by the link of single integral process of creation and management of the material flows. We propose formation of sub-system of the elements of road and transportation components with their further unification by a single road transportation system. Inter-connected elements of the system are formalized in the form of dispersed two-phase system of mass service. Each element of the system is evaluated by its own characteristics. Practical value. The practical significance of research consists in possibility of their use by employees of motor transport enterprises, service enterprises, responsible for procurement of production and transportation of products, travel agencies to make science-based decisions in forming the program of road works and to provide alternative opportunities for the rational organization of cargo transportation.

The backbone of urban street networks: Degree distribution and connectivity characteristics

This article explores the backbone of urban street networks to reflect the characteristics of the overall network. The model representing the connection of urban road elements based on traffic properties is constructed and then applied to the traffic network in Xiamen, China. The backbone of urban street networks comprises road elements whose hierarchical measure is greater than 1 and named roads in this context. And the difference between the overall road network and the backbone is compared from the perspective of degree distribution and connection characteristics. The results reveal that the backbone (hierarchical measure > 1) of the urban street network is consistent with the overall road network. The skeleton road network in this article saves the amount of work for road elements by 17.75%, and the intersection elements by 4.21%. Our conclusions will be beneficial to assess the current network performance more efficiently and improve existing road network systems as well as discovering the complicated relationship between network structure and dynamic behaviors.

Cyclographic Modeling of Surface Forms of Highways

A cyclographic approach towards the formation of a highway surface is suggested. The approach is based on mapping a point (x, y, z) of the space R3 onto a cycle (a circle with direction) in the plane ∏1 (xy). The centre of the cycle is a point (x, y) and its radius is defined as R = ±|z|. In case z > 0, the cycle radius R = z and the cycle has one direction. In case z < 0, the cycle radius R = −|z| and the cycle has the opposite direction. Thus, a one-to-one correspondence is established between the set of ∞3 points of the space R3 and the set of ∞3 cycles of the plane (xy).The main linear element of a road is its axis which in general is a spatial curve. The spatial forms of road elements are a roadway, road shoulders, slopes; they are determined by the main linear element. Proceeding from this principle of formation of geometric and mathematical models of road elements spatial forms, the use of road axis cyclographic projection is proposed. The parametric equations of the envelope of cycles modeling the axis point in the plane are obtained for the general case of cyclographic mapping. In a general case, unlike the classic one, the use of regular angle variation at the vertex of mapping cones is suggested. Taking the envelope of cycles and the axis of the road as the guidelines for the surface, the surface forms of road elements are obtained in the form of developable surfaces. The presence of two modifications of road elements’ surface forms distinguishes the cyclographic approach from existing ones and gives additional possibilities for the choice of optimal surface forms in the design of highways.

The best way to assess visually induced motion sickness in a fixed-base driving simulator

ObjectiveDriving simulator usage is becoming more widespread, yet many users still experience substantial motion sickness-like symptoms induced by optical flow, called visually induced motion sickness (VIMS). The Fast Motion sickness Scale (FMS) allows for continuous on-line assessment of VIMS. Using mixed models for ordinal data, this study investigated how to optimally analyze FMS data, and then used the resulting models to examine the development of symptoms over time in detail. Additionally, the study explored the impact of specific VIMS-inducing road elements. MethodsTwenty-eight healthy young adults without prior simulator experience completed six courses on two days in a fixed-base driving simulator. VIMS severity was reported every minute using the FMS. Each course included two road elements designed to induce VIMS. The data was analyzed using cumulative link mixed models. ResultsThe FMS data deviated clearly from a normal distribution. Treating FMS data as ordinal led to preferable models compared to models assuming interval scale. VIMS increased within each drive and over consecutive courses, but decreased between two days separated by a week (adaptation). Adaptation was attributable to less pronounced symptom increases on the second day, both within each course and between consecutive drives. VIMS increases within each drive were less pronounced during later courses of each day (habituation). Participants differed both in general symptom levels and in their progressions of VIMS over time. Additionally, VIMS-inducing road segments could be identified as leading to higher probabilities of symptom increases. ConclusionMixed models analyses of FMS data from repeated VIMS measurements can benefit from taking deviations from normal distribution and interval scale into account. The gained insights into habituation and adaptation processes, as well as into the impact of specific road elements, can help in planning and conducting future driving simulator experiments.

Investigating Car Users’ Driving Behaviour through Speed Analysis

Speed has been identified for a long time as a key risk factor in road traffic: inappropriate speeds contribute to a relevant part of traffic accidents. Many literature studies have focused on the relationship between speed and accident risk. Starting from this consideration this paper investigates traffic accident risk by analysing the travelling speeds recorded by real tests on the road. A survey was conducted to collect experimental speed values in a real context. A specific road segment, belonging to an Italian rural two-lane road, was repeatedly run by 27 drivers in order to collect the instantaneous speed values for each trajectory. Smartphone-equipped vehicles were used to record continuous speed data. The recorded data were used to calculate: the average speed, 50th and 85th percentile speed for each geometric element of the analysed road segment. The main result of the research is the classification of car users’ driving behaviour based on the speed values. By using the above mentioned ranges of speed, the classification provides three types of driving behaviour: safe, unsafe, and safe but potentially dangerous. It was found that only four drivers feature “safe” behaviour, driving in a safe manner on most of the road elements. However, the major part of drivers, even if they feature safe behaviour, could be dangerous for other drivers because they drive at very low speeds.

Łódź in the regional and national transportation system

This article presents the location of Łódź in the transport network of Poland and the Łódź region. It focuses on the centre’s location in reference to the main elements of road, rail and air networks on a national and regional scale. Due to physical and geographical location of Łódź, the three branches of transport exhaust the city’s transport possibilities. Besides that, transport relations of Łódź are characterized as far as the functioning public transport is concerned, considering all the aforementioned modes of transport. The study also includes information on the significance of Łódź as a transport node for cargo transport. All these analyses precede reflections on the location of Łódź against the background of trans-European transport corridors as well as an overview of historical conditioning of transport connections of the area of today’s Łódź.

Detecting Different Road Infrastructural Elements Based on the Stochastic Characterization of Speed Patterns

The automatic detection of road related information using data from sensors while driving has many potential applications such as traffic congestion detection or automatic routable map generation. This paper focuses on the automatic detection of road elements based on GPS data from on-vehicle systems. A new algorithm is developed that uses the total variation distance instead of the statistical moments to improve the classification accuracy. The algorithm is validated for detecting traffic lights, roundabouts, and street-crossings in a real scenario and the obtained accuracy (0.75) improves the best results using previous approaches based on statistical moments based features (0.71). Each road element to be detected is characterized as a vector of speeds measured when a driver goes through it. We first eliminate the speed samples in congested traffic conditions which are not comparable with clear traffic conditions and would contaminate the dataset. Then, we calculate the probability mass function for the speed (in 1 m/s intervals) at each point. The total variation distance is then used to find the similarity among different points of interest (which can contain a similar road element or a different one). Finally, a k-NN approach is used for assigning a class to each unlabelled element.

Capturing Cultural Differences between UK and Malaysian Drivers to Inform the Design of In-Vehicle Navigation Systems

Attending to cultural diversity is important for products and technology intended for global placement, such as automobiles, yet many products (and associated interfaces) lack genuine cultural differentiation. For example, in-vehicle navigation systems are typically identical in form and function across world markets, differing only in the local language and map database. To capture and explore culturally-salient design factors, we utilised a scenario-based design methodology, involving 6 experienced drivers from the UK and Malaysia. Participants were asked to portray their ideal navigation system interface designs – by drawing pictograms and devising accompanying spoken messages – to direct drivers along 3 prescribed routes in the UK, Malaysia and Japan. Routes were presented using video and paper maps, with the order of presentation counterbalanced between groups; participants were not told in advance from which country each route was derived. Proposed designs highlight differences at a country level, which are consequently interpreted from a cultural perspective. For example, Malaysian drivers included a higher density of navigational elements in their designs, particularly in their home environment, compared to UK drivers. Malaysian drivers also created more incremental designs, particularly on the approach to a manoeuvre, suggesting a desire for greater navigational support at this point in the journey. Landmarks were consistently incorporated in designs, but differences were noted in cultural salience. Additionally, the phrasing of instructions (e.g. “go straight on”), nomenclature for road elements (e.g. ‘roundabout’) and distance declaration conventions (e.g. units) differed at a country level. The findings can be used to inform the design of culturally-attuned in-vehicle navigation systems.

Operating Speed Models for Tangent Segments on Urban Roads

Information about operating speeds is essential to design better roads, model traffic emissions, and ensure design consistency while efficient and safe operations on roads are maintained. Therefore, understanding how different factors affect operating speeds and developing operating speed prediction models are critical research issues. Many studies have developed such models on rural roads and highways, but only a few studies have considered development of such models on urban roads and fewer still on tangential segments. This present study attempted to address these limitations by developing operating speed models with data from 249 tangential road segments in the city of Edmonton, Alberta, Canada. A generalized linear model was developed with panel data, and the primary aim was to explore the relationships between operating speeds on urban roads and features of the road environment. To study the impact of road elements on different road types, three models were created: one that combined arterial and collector locations, one for arterials only, and one for collector roads only. The results revealed that roads with sidewalks that were farther away from the road and with low object density or tree density were all associated with higher operating speeds. Locations with monolithic walks on both sides of the road had lower operating speeds. Furthermore, operating speeds decreased as access increased, while longer roads had higher operating speeds. One major takeaway was that the elements differed between road classes. The two variables, which stood out in that respect, were medians and bus stops.

Landslide susceptibility mapping by using fuzzy logic: a case study of Cham-gardalan catchment, Ilam, Iran

Landslides are introduced as regional movements, which influence different engineering structures such as roads, railways, and dams and cause the person’s death. Identification of landslide zones may decrease the financial losses and human injuries or deaths. This study tries to achieve a landslide susceptibility mapping in Cham-gardalan catchment by weighting the main criteria and the membership functions of fuzzy logic. For this, we applied the best relationship function between the presence and absence of landslides as well as a collection of the elements. At first, the landslide points were identified by the means of some components those of satellite images, topographical (1:50,000) and geographical (1:100,000) maps, field visits, and Google Earth software followed by the preparation of landslide distribution maps. Then, all effective landslide factors such as percentage of slope, slope aspect, height, geology, land uses, distance from roads, distance from drainages, distance from breakage, and precipitation map have been utilized in order to conduct the fuzzy analyses. Landslide susceptibility map was performed by fuzzy operators (Gamma, Product, Sum, Or, And) in the study area. After fuzzificating and weighting, the effective criteria of landslides were determined through fuzzy Gamma operators with the landaus of 0.2, 0.5, 0.8, and 0.9 and by comparing final maps for making an appropriate model of landslide susceptibility mapping. The regional susceptibility map represents the landslide-prone areas in five categories those of very low, low, moderate, high, and very high. Our results indicated that among the applied operators, Gamma with landau of 0.9 can be used as an appropriate method for mapping the landslide susceptibility due to the suitable fuzzification of given criteria based on landslide distribution maps. In addition, the elements of road, percentage of slope, distance from drainage, and geology were recognized as the most important factors for occurring the landslides.

Reduction of GPS Latency Using RTK GPS/GNSS Correction and Map Matching in a Car NavigationSystem

The difference between definition time of GPS (Global Positioning System) position data and actual display time of car positions on a map could reduce the accuracy of car positions displayed in PND (Portable Navigation Device)-type CNS (Car Navigation System). Due to the time difference, the position of the car displayed on the map is not its current position, so an improved method to fix these problems is required. It is expected that a method that uses predicted future positionsto compensate for the delay caused by processing and display of the received GPS signals could mitigate these problems. Therefore, in this study an analysis was conducted tocorrect late processing problems of map positions by mapmatching using a Kalman filter with only GPS position data anda RRF (Road Reduction Filter) technique in a light-weight CNS. The effects on routing services are examined by analyzing differences that are decomposed into along and across the road elements relative to the direction of advancing car. The results indicate that it is possible to improve the positional accuracy in the along-the-road direction of a light-weight CNS device that uses only GPS position data, by applying a Kalman filter and RRF.

OPERATING SPEED AS A KEY FACTOR IN STUDYING THE DRIVER BEHAVIOUR IN A RURAL CONTEXT

The research aims to explore the effects of geometric road features on driver speed behaviour in order to identify unsafe road segments where high reductions in speed between successive road elements occur. The sample involves two-lane rural roads on flat terrain (vertical grade less than 5%) in Southern Italy, totalling 184 km without spiral transition curves between the tangent segments and circular elements. The testing was carried out on 567 study sites, of which 248 are on circular curves and 319 on tangents. Speed data collection was carried out in environmental and traffic conditions using a laser. The conditions were the following: dry roads, free flow conditions, daylight hours and good weather conditions. The main goal was to calibrate and validate different operating speed prediction models: a) one model on tangent segments; b) one model on circular curves; c) only one model to be used at the same time on tangents and circular curves. The validation process involved almost 10% of the total road network length, that was removed from the calibration phase. The speed measurements of each of the first two datasets (a, b) were grouped into ten homogeneous substrates while for the remaining dataset (c) sixteen substrates were defined by using a hard c-means algorithm. Two statistical criteria were used to remove anomalous operating speed values from each group of three datasets, namely, the Chauvenet criterion and the Vivatrat method. The first criterion was preferred in the final process of model selection. The results of the first filtering procedure showed more homogeneous samples that guaranteed a higher correlation coefficient and lower residuals of the predictive models during the validation phase than the Vivatrat method. The models were developed using an Ordinary Least Squares (OLS) method. The explanatory variables were total segment length, lane width, curvature of the road element, the curvature change rate on homogeneous road segments, and the number of residential driveways per km. ANOVA and additional synthetic statistical parameters were assessed to check the effectiveness of using a single general model to predict operating speeds at the same time on tangents and on circular curves alike. The results suggested the reliability of this hypothesis and its effectiveness in bringing advantages during the application phase.

ROAD NETWORK EXTRACTION FROM DSM BY MATHEMATICAL MORPHOLOGY AND REASONING

The objective of this research is the automatic extraction of the road network in a scene of the urban area from a high resolution digital surface model (DSM). Automatic road extraction and modeling from remote sensed data has been studied for more than one decade. The methods vary greatly due to the differences of data types, regions, resolutions et al. An advanced automatic road network extraction scheme is proposed to address the issues of tedium steps on segmentation, recognition and grouping. It is on the basis of a geometric road model which describes a multiple-level structure. The 0-dimension element is intersection. The 1-dimension elements are central line and side. The 2-dimension element is plane, which is generated from the 1-dimension elements. The key feature of the presented approach is the cross validation for the three road elements which goes through the entire procedure of their extraction. The advantage of our model and method is that linear elements of the road can be derived directly, without any complex, non-robust connection hypothesis. An example of Japanese scene is presented to display the procedure and the performance of the approach.

ROAD NETWORK EXTRACTION FROM DSM BY MATHEMATICAL MORPHOLOGY AND REASONING

Abstract. The objective of this research is the automatic extraction of the road network in a scene of the urban area from a high resolution digital surface model (DSM). Automatic road extraction and modeling from remote sensed data has been studied for more than one decade. The methods vary greatly due to the differences of data types, regions, resolutions et al. An advanced automatic road network extraction scheme is proposed to address the issues of tedium steps on segmentation, recognition and grouping. It is on the basis of a geometric road model which describes a multiple-level structure. The 0-dimension element is intersection. The 1-dimension elements are central line and side. The 2-dimension element is plane, which is generated from the 1-dimension elements. The key feature of the presented approach is the cross validation for the three road elements which goes through the entire procedure of their extraction. The advantage of our model and method is that linear elements of the road can be derived directly, without any complex, non-robust connection hypothesis. An example of Japanese scene is presented to display the procedure and the performance of the approach.

A new method for road detection in urban areas using high-resolution satellite images and Lidar data based on fuzzy nearest-neighbor classification and optimal features

Detection of roads in urban areas is of greater importance and is a persistent research focus in the remote sensing community. The spectral and geometrical varieties of road pixels; their spectral similarity to other features such as buildings, parking lots, and sidewalks; and the occasional obstruction by vehicles and trees are obstacles to the precise identification of urban roads through satellite images. Lidar data, however, provide height information that can facilitate the identification of roads from other spectrally similar elements. Therefore, Lidar has been widely used alongside satellite images to identify features such as roads. In this paper, high-resolution QuickBird satellite imagery and Lidar data processed through nearest-neighbor classification based on optimal features have been used together to extract various types of urban roads. This work designed and implemented a rule-oriented strategy based on a masking approach. A supplementary strategy based on optimal design features was also used. The overall precision of class identification is 91 % with a kappa coefficient of 0.87, which shows a satisfactory precision according to different conditions and considerable interclass noise. The final results demonstrate the high capability of object-oriented methods in simultaneous identification of a wide variety of road elements in complex urban areas using both high-resolution satellite imagery and Lidar data.

Flexible Stochastic Frontier Approach to Predict Spot Speed in Two-Lane Highways

The approach to spot speed prediction in two-lane highways followed in this study aims to evaluate the effects of a comprehensive set of speed factors, with a special focus on the geometric characteristics of the road segment to which the element belongs. Two flexible models were developed for different types of roads based on a stochastic frontier formulation in which the maximum operating speed is estimated as a function of road geometrics, and the one-sided disturbance accounts for diversity in driving behavior and vehicle characteristics, allowing the estimation of any percentile speed. The models are applicable to horizontal curves and tangents and consider both on-site characteristics and aggregated variables characterizing the road segment. The results show a clear influence of segment features on different percentile spot speeds, revealing that recent driving experience and expectations about the quality of the geometric design influence the way a driver approaches a specific road element. Additionally, this study contributes to addressing some of the limitations of existing speed models identified in the literature.

Evaluating Driver Distraction Factors in Urban Motorways. A Naturalistic Study Conducted in Attica Tollway, Greece

Over the last years, distracted driving possesses a leading position among accident causes and it constitutes an increasing road safety problem with disastrous results. Considering external factors of distraction as highly significant, they can be grouped in four categories: built roadway, situational entities, natural environment, and built environment. The fourth category, related to civil infrastructure and commercial land use, combined with high vehicle speeds that occur in motorways, might contribute to the creation of a very dangerous environment, increasing driver distraction and inattention. Through accurate research, solid results can emerge and traffic safety can be enhanced. The present study deals with driver distraction caused by out-of-the-vehicle factors, as well as factors related to the driver, such as age, gender, driving experience etc. It covers the distraction of driver attention during driving due to external factors that are not related to the main task of driving, resulting in impairments to driver attention and decision-making ability and hence the driver’s overall performance. For this purpose, we assess the side effects of numerous road elements, such as information signs, roadside advertising, Variable Message Signs, toll buildings, noise barriers/panels etc. to driver attention. The study is based on a medium-scale experimental procedure which took place in Attica Tollway, the Ring Road of the Athens metropolitan area, which was part of a larger research project conducted by the University of Thessaly, Department of Civil Engineering that included a total of three urban freeways in Greece. In order to create the appropriate research basis and to use as reliable data as possible, the gaze tracker FaceLab software was used on a sample of 29 drivers. Each participant drove 51 km on Attica Tollway, both in level terrain with 3 lanes and speed limit up to 120 km/h and in rolling terrain with 2 lanes and speed limit up to 80 km/h. The distraction of driver attention is evaluated via a continuous recording of his/her gaze, which acts as the main indicator regarding driver performance. The results of this procedure, analyzed via Captive software, are focused on the time that the driver’s gaze remained on each of the road elements under research. The analysis offers conclusions on different aspects - driver, road element and the road in total - comparing and categorizing the results by using a 4-level timescale from 0 to 2 seconds. This study can be used as a tool that can help in understanding and limiting the use of roadside elements that are not related to the execution of the driving task, but that may serve as potential causes of distraction. The results of this type of research procedures are very useful in preventing the forthcoming pressure for more billboards and trademarks on the roads, as well as in encouraging the adaptation of more precise regulations relating to the road infrastructure, the placement of roadside elements, etc.

Improving Safety of Transportation by Using Intelligent Transport Systems

As the intelligent railway is the trend of current development, the paper aims to show an overview of some examples of intelligent systems and their functions that could help to protect transportation infrastructure. The paper deals with importance of critical transportation infrastructure and ways to protect it. Intelligent transportation systems are advanced tools to improve and support protection of critical infrastructure elements. The main purpose is to define intelligent transportation systems which could be used to protect elements of critical road and rail transportation infrastructure. Protection of critical transportation infrastructure is very complex issue. It is not difficult to identify a large number of critical infrastructure elements. The question is: “How to protect/ensure them?” A compromise between funding of protection and finding really critical elements is to be found. There are many systems that could be used to make infrastructure and whole transportation safer. A lot of projects are dealing with building new systems, architecture of management system that could help users to manage traffic.

Application of a Network Safety Management Tool in Urban Areas: Zurich, Switzerland, Case Study

Because of the economic and social cost of traffic accidents, it is essential for road administrators to evaluate where infrastructure investments are necessary to improve the system. Network safety management (NSM) is an analysis tool typically used on freeways and other interurban roads to identify the locations with the highest potential for infrastructure improvements from a safety perspective. A study was done on how this tool could also be used to identify such locations within an urban environment. The area of study was the city of Zurich, Switzerland, and the accident data were for the period 2009 to 2013. The aim was to investigate the application of NSM in urban environments, illustrate it with a real case study, evaluate the results obtained, and test robustness of the results for different input parameters. To do this, georeferenced data were required to have explicit distinctions between the three road network elements used: primary road segments, intersections, and residential zones. On the basis of different accident cost rates, a prioritization of the individual network elements was made. Results show that mostly network elements with numerous conflict points have the highest safety potential. Further tests reveal that traffic volume is the most influential parameter within the model. Additionally, more differentiated cost rates are presented, and a comparison with the road safety tool Black Spot Management is employed to verify the detected accident clusters. The findings are used to make pragmatic recommendations on the use of NSM in an urban context.