Road Centerline Research Articles

The Impact of Removing Centerline Barriers from Highway–Rail Grade Crossings on Drivers’ Violations

The objective of this study was to assess changes in drivers’ unsafe maneuvers after removal of a centerline barrier installed at a dual-quadrant gated highway–rail grade crossing to improve safety. Such barriers limit drivers’ ability to pass around closed dual-quadrant gates, thereby reducing the possibility of motor vehicle collisions with trains. Highway safety-related appurtenances installed as countermeasures are usually left in place for extended periods, and the effects of their removal are not well researched. The removal of a barrier installed along the road centerline at a highway–rail grade crossing in Nebraska provided the opportunity to investigate the accompanying changes in drivers’ violations. Analysis of data collected before and after removal of the barrier showed that unsafe driver maneuvers increased after removal of the barrier. Specifically, passing around dual-quadrant gates with an oncoming train and making U turns to drive away from the closed crossing increased. The conclusion is that barrier removal contributed to the increase in unsafe driver maneuvers at the studied highway–rail grade crossing. Although limited in scope, this study lends credibility to the practice of not removing an effective countermeasure once installed, though regular maintenance is a requisite for continued effectiveness.

Procedure to Determine the Geometry of Road Alignment Using GPS Data

Traffic safety and road geometry are strictly interlinked because road geometry deeply influences the drivers’ performance. So it is very important to know road alignments geometry. Road centreline data for the geometry definition can be generally collected from existing maps or by static measurements (traditional surveys) or by dynamic measurements (GPS receiver mounted on a car). The procedure to define the road geometry, independently from the survey technique and the data type, must be implemented considering the precision level necessary to road applications. This study tries to define intrinsic limits of this integrated data measurement and processing procedure, with the aim to define the reliability of road alignment geometry according to the final employing of road geometry recognition.

수치지도의 도로명주소 체계 연계를 위한 매칭 및 속성 융합 방안 - 도로중심선 레이어를 중심으로 -

The Road Name Address system has begun to be applied and widely used since 2011. However, the Digital Map, or the national representative basic map, has no reference to the Road Name Address system. It causes some difficulties to use the Digital Map under the Road Name Address system. In this paper, we suggest a method for generating the expanded Digital Map by adding information about Road Name Address system into the objects of the Digital Map. First, object matching pairs between the road section layer from the Road Name Address Map and the road centerline layer from the Digital Map are found. Then attributes to be copied from the Road Name Address map to the Digital Map are extracted by comparing their attribute tables. Finally the extracted attributes are copied from the Road Name Address Map to the Digital Map. The expanded road centerline layer of the Digital Map then has attributes about road name according to the Road Name Address system, so that the georeferencing of the Digital Map according to the Road Name Address system becomes possible.

TOWARDS INTRODUCING A GEOCODING INFORMATION SYSTEM FOR GREENLAND

Abstract. Currently, addressing practices in Greenland do not support geocoding. Addressing points on a map by geographic coordinates is vital for emergency services such as police and ambulance for avoiding ambiguities in finding incident locations (Government of Greenland, 2010) Therefore, it is necessary to investigate the current addressing practices in Greenland. Asiaq (Asiaq, 2011) is a public enterprise of the Government of Greenland which holds three separate databases regards addressing and place references: – list of locality names (towns, villages, farms), – technical base maps (including road center lines not connected with names, and buildings), – the NIN registry (The Land Use Register of Greenland - holds information on the land allotments and buildings in Greenland). The main problem is that these data sets are not interconnected, thus making it impossible to address a point in a map with geographic coordinates in a standardized way. The possible solutions suffer from the fact that Greenland has a scattered habitation pattern and the generalization of the address assignment schema is a difficult task. A schema would be developed according to the characteristics of the settlement pattern, e.g. cities, remote locations and place names. The aim is to propose an ontology for a common postal address system for Greenland. The main part of the research is dedicated to the current system and user requirement engineering. This allowed us to design a conceptual database model which corresponds to the user requirements, and implement a small scale prototype. Furthermore, our research includes resemblance findings in Danish and Greenland's addressing practices, data dictionary for establishing Greenland addressing system's logical model and enhanced entity relationship diagram. This initial prototype of the Greenland addressing system could be used to evaluate and build the full architecture of the addressing information system for Greenland. Using software engineering methods the implementation can be done according to the developed data model and initial database prototype. Development of the Greenland addressing system using a modern GIS and database technology would ease the work and improve the quality of public services such as: postal delivery, emergency response, customer/business relationship management, administration of land, utility planning and maintenance and public statistical data analysis.

NETWORK SNAKES FOR ADAPTING GIS ROADS TO HEIGHT DATA OF DIFFERENT DATA SOURCES – PERFORMANCE ANALYSIS USING ALS DATA AND STEREO IMAGES

Abstract. In order to tackle the problem of consistently integrating 2D vector data and a DTM, we presented an approach for the adaptation of 2D GIS road objects to airborne laser scanning (ALS) data using active contours (snakes) in (Göpfert et al., 2011). In this paper the algorithm is modified for the integration of stereo images as an alternative data source for area-wide height information. For that reason, a new image energy is developed that exploits geometric and radiometric features derived from the image data. Afterwards, we compare the applicability of our method with respect to the ALS data and stereo images as input. In addition, a new approach is suggested that analyses the different energy terms of active contours after the optimisation process in order to automatically detect contour parts that did not reach a suitable position in the sensor data. This concept of an internal evaluation is able to guide the user during post processing. Experiments show that the snake approach with an image energy based on stereo images is generally able to adapt GIS road centrelines to the sensor data and thus to improve the quality of the 2D vector data. However, the comparison to the results for ALS data demonstrates that the algorithm perform slightly worse for image data in the high precision level.

Object-Space Road Extraction in Rural Areas Using Stereoscopic Aerial Images

This letter proposes a semiautomatic method for 3-D road extraction in rural areas using stereoscopic aerial images. A strategy based on the dynamic programming algorithm provides a solution to the road extraction problem in the object space. The direct tracing of road centerlines in the object space necessitates mathematical relationships connecting road points in the stereoscopic image spaces and in the object space, enabling integration of radiometric information from the stereoscopic images into the associated energy function. The extraction process begins by first measuring a few seed points in one image of the stereoscopic pair and then transforming these into the object-space reference system. Experimental results show that the proposed method was efficient and usually provided accurate road centerlines.

Adaptive scale smoothing for road redundancy region elimination

In the process of road extraction, the road region often mixes with some redundancies caused by the phenomenon of different objects with the same spectrum, which exists widely in remote sensing images. To eliminate these redundancies and preserve neat and accurate road regions, a method based on skeleton analysis is proposed. At first, the shortest path of a specified road segment is constructed with mixed region skeletons. The road width at the skeleton point is then selected as the smoothing scale on this point, on which basis an accumulative and bidirectional smoothing is taken. With the smoothed path and its average width, a buffer algorithm reconstructs the road region. The results show that redundancies of the road can be eliminated correctly, and accurate road center lines and neat road regions can be obtained.

A template-matching based approach for extraction of roads from very high-resolution remotely sensed imagery

Automated or semi-automated extraction of road networks is a prerequisite to fast acquisition and update of geospatial data. Actually, line-shaped lane markings and/or median strips on road surfaces are less impacted by occlusions of vehicles or shadows of trees than the other parts of road surfaces on very high-resolution (VHR) remotely sensed imagery. These features provide a clue for road extraction. This article proposes an approach for semi-automated extraction of road networks by tracking apparent lane markings and/or median strips on VHR imagery. After preprocessing the raw image, three seed points on a short road segment are manually selected, which indicate starting point, direction and width of the road, respectively. Based on the manually selected data, a reference template of the road, which is composed of two components: a cross-section profile, rectangular templates of lane markings and median strips, is created. With the created reference template, automated road tracking is triggered. During the process of road tracking, a least-squares template matching is employed to search the optimal road centreline points, and a human operator is retained in the loop to guide the computer. The above operation is repeated until an entire road network is completely extracted. Tests of the above-proposed method are conducted on both aerial and VHR satellite imagery. The results show that the proposed method can successfully track over 94% of the highways and 81% of the arterial roads from the VHR images, and save the time of 26% when comparing to traditional methods.

GIS 프로그래밍을 이용한 도로중심선 평면선형 평가

The horizontal alignment of road is deeply related with the stability of the road and traffic capacity. It is necessary to analyze horizontal alignment of road accurately for efficient maintenance of the road and relevance judgment about the standard. Recently the study on horizontal alignment of road using Lidar data and GPS was concluded, but they were many problem analyzing horizontal alignment radius of curvature in wide area. In this study, the tool which the radius of curvature can evaluate the suitability about Rules about the Road Structure & Facilities Standards by using center lines of the road of the digital map tries to implement on GIS. The interface was designed and implemented which can automatically estimate the Road Centerline Horizontal Alignment by using .

Steering Control of an Autonomous Vehicle Based on RBF Neural Networks Compensation and Dynamic Systems

A tracking controller based on RBF (Radial Basis Function) neural networks compensating in vision based autonomous vehicles is designed in this paper. One input of the RBF compensating model are the lateral offset which measured by the vision system as the distance between the road centerline and the center of the vehicle a certain distance before. Another input is the steering angle which was collected when the vehicle was driving by a human testing driver. The controller is finally made by linearly fitting the parameter of the RBF neural networks. The stability is proven by composite Lyapunov functions. The robustness of the controlled system is theoretically investigated with respect to speed variations and uncertain vehicle physical parameters. Several simulations are made on a sedan vehicle to prove the effectiveness of this controller when perform path tracking on roads with an uncertain curvature.

Integrated Driver and Active Steering Control for Vision-Based Lane Keeping

A nested PID steering control for autonomous vehicles equipped with artificial vision systems is designed so that the driver can override the automatic lane-keeping action and obtain a complete control of the vehicle lateral dynamics without any switching strategy. The control input is the steering wheel angle: it is designed on the basis of the yaw rate, which is measured by a gyroscope, and the lateral offset, which is measured by the vision system as the distance between the road centerline and a virtual point at a fixed distance ahead from the vehicle. No lateral acceleration and no lateral speed measurements are required. A PI active front steering control on the basis of the yaw rate tracking error is designed to compensate for constant disturbances while improving vehicle steering dynamics and reducing the influence of parameter variations. The yaw rate reference is viewed as the control input in an external control loop: it is designed using a PID control based on the lateral offset measurements to reject the disturbances on the curvature during autonomous control, i.e., when the driver is not exerting any torque on the steering wheel. A third control block is designed to allow the driver to control the vehicle (for example, lane change for passing purposes or obstacle avoidance) overriding the automatic lane-keeping action while maintaining the advantages of the yaw rate feedback. Several simulations are carried out on a standard big sedan CarSim vehicle model to explore the robustness with respect to unmodelled effects such as combined latera land longitudinal tire forces, pitch and roll and parameters variations. The simulations show reduced path following errors and new stable manoeuvres in comparison with the model predictive steering controller implemented by CarSim in both cases of autonomous and non autonomous control.

Semi-Automatic Road Tracking using Parallel Angular Texture Signature

Road tracking is a promising technique to increase the efficiency of road mapping. In this paper, a semi-automatic road tracker, Parallel Angular Texture Signature (PATS), is presented. The tracker is object-oriented in some sense, because it makes best use of the texture signature of road primitives on high-resolution remotely sensed imagery. Our tracker uses parabolas to model the road trajectory and predicts the position of next road centerline point. It employs PATS to get the moving direction of current road centerline point, and it will move on one predefined step along the moving direction to reach a new position, and then it uses curvature change to verify the newly added road point. Moreover, we also build compactness of Angular Texture Signature polygon to check whether the PATS is suitable for subsequent tracking. Repeat the above steps until the whole task is finished. Extensive experiments demonstrate that the proposed tracker is capable of efficiently extracting most of main roads from medium and low resolution imagery, and reliably and robustly extracting most of ribbon roads from high resolution SAR and optical imagery.

Semiautomatic extraction of main road centrelines in aerial images acquired over rural areas

In this article, a scheme for road extraction in rural areas is proposed based on a search of the road centrelines. For this purpose, the road centreline is modelled as being a chain composed of short line segments. Only small angles are allowed between adjacent segments. In order to find the next element, the Radon transform is applied. Experiments using this approach are described and the results are compared to vectors obtained by visual analysis of the image on the screen. The accuracy of the semi-automated method is evaluated considering the completeness, correctness and root mean square of extracted centrelines.

Sliding‐mode control for automated lane guidance of heavy vehicle

SUMMARYIn the present work, an active steering assistance system for heavy vehicles is developed to prevent lane departure and let the vehicle follow the road's centre line. The controller is based on the super‐twisting algorithm. An estimator based on the sliding mode observer is also developed to estimate the vehicle dynamics. The lateral positions and speeds are then controlled to keep the vehicle in the centre of the lane. The lateral offset and the relative yaw angle are supposed to be measured and the road curvature to be known. Some simulation results are given to show the quality of this steering assistance system. Copyright © 2011 John Wiley & Sons, Ltd.

Towards an automatic system for road lane marking extraction in large-scale aerial images acquired over rural areas by hierarchical image analysis and Gabor filter

An automatic approach to road lane marking extraction from high-resolution aerial images is proposed, which can automatically detect the road surfaces in rural areas based on hierarchical image analysis. The procedure is facilitated by the road centrelines obtained from low-resolution images. The lane markings are further extracted on the generated road surfaces with 2D Gabor filters. The proposed method is applied on the aerial images of the Bruce Highway around Gympie, Queensland. Evaluation of the generated road surfaces and lane markings using four representative test fields has validated the proposed method.

Semi-automatic road tracking by template matching and distance transformation in urban areas

Road surfaces are seriously disturbed by a variety of types of noise on very high resolution (VHR) remotely sensed imagery in urban areas, which is a tough challenge for most road tracking methods. In fact, the sizes of most types of noise such as vehicles, zebra crossings and lane markings are smaller than the width of road surfaces on VHR images. In this sense, some filtering techniques are helpful to weaken the negative effects of these types of image noise. In this article, a semi-automatic method is proposed to track roads on VHR imagery. Once a human operator inputs a seed point on a selected road, the spoke wheel algorithm is used to obtain road direction, road width and starting point, and generate a reference template. Then the automatic tracking is triggered. During the process, a reference template is moved to generate several target templates. For each target template, the differences of grey values between the reference template and the target template are calculated, and then thresholding is used to create a binary template. Subsequently, Euclidean distance transformation (EDT) is used to erode the small disturbing noises on each binary template, which is helpful to search optimal road centreline points. The above tracking process is repeated until a whole road network is completed. A QuickBird image covering Tai'an area is used for the test. The results demonstrate that our improved method can extract urban road networks more reliably, more robustly and faster than applying the least-squares template matching method.

Estimation of Road Centerline Curvature from Raw GPS Data

Development and wide use of route guidance systems lead to the need for suitable digital maps that can be used for some advanced applications. Sufficient accuracy of road geometry with emphasis on road centerline positions and curvature is crucial. In this paper is presented a method for finding road centerline curvature from raw GPS data. The approach consists of a few processing steps. First it is necessary to fit raw data of each road section using B-splines, and generate equidistant vertices of polyline of the fitted curve. Then follows the appliance of stereographic projection of chosen polyline segments onto the unit sphere. Using the least square method, the plane that best fits the points on the unit sphere is found and the circle that is the intersection of the plane and the unit sphere. Stereographic projection of this circle back to the equatorial plane gives the corresponding circular arc and curvature. The method is also applicable in higher dimensions. The 3D case is numerically presented and results show that the proposed procedure is efficient and yields accurate results.

Nested PID steering control for lane keeping in autonomous vehicles

In this paper a nested PID steering control in vision based autonomous vehicles is designed and experimentally tested to perform path following in the case of roads with an uncertain curvature. The control input is the steering wheel angle: it is designed on the basis of the yaw rate, measured by a gyroscope, and the lateral offset, measured by the vision system as the distance between the road centerline and a virtual point at a fixed distance from the vehicle. No lateral acceleration and no lateral speed measurements are required. A PI active front steering control based on the yaw rate tracking error is used to improve the vehicle steering dynamics. The yaw rate reference is computed by an external control loop which is designed using a PID control with a double integral action based on the lateral offset to reject the disturbances on the curvature which increase linearly with respect to time. The proposed control scheme leads to a nested architecture with two independent control loops that allows us to design standard PID controls in a multivariable context (two outputs, one input). The robustness of the controlled system is theoretically investigated with respect to speed variations and uncertain vehicle physical parameters. Several simulations are carried out on a standard big sedan CarSim vehicle model to explore the robustness with respect to unmodelled effects. The simulations show reduced lateral offset and new stable μ - split braking maneuvres in comparison with the model predictive steering controller implemented by CarSim. Finally the proposed control law is successfully tested by experiments using a Peugeot 307 prototype vehicle on the test track in Satory, 20 km west of Paris.

Association Between Proximity to Traffic and Type 2 Diabetes: The Multiethnic Study of Atherosclerosis

PP-29-030 Background/Aims: Although particulate matter has been suggested as a possible risk factor for type 2 diabetes onset, few epidemiologic studies and no longitudinal studies, have been reported. We investigated the associations of proximity to a major roadway, which is a surrogate of traffic pollution exposure with incident of type 2 diabetes and longitudinal changes in fasting serum glucose in multiethnic study of atherosclerosis. Methods: Between 2000 and 2007, we examined 4676 participants free of type 2 diabetes at baseline with a total of 18,479 observations (mean number of exams = 2.5). Type 2 diabetes was defined as fasting glucose of ≥126 mg/dL at any exam or use of antidiabetes medication. At baseline (2000–2002), traffic-related pollution exposure was estimated based on participant's residential proximity to a major roadway (a binary variable based on whether the participant resided within 100 m of the centerline of a highway or within 50 m of the centerline of a major arterial road). Linear mixed models and interval-censored survival analyses were used to model longitudinal changes in fasting glucose (log-transformed) and incident type 2 diabetes, respectively, adjusting for age, gender, race/ethnicity, education, body mass index, waist circumference, cigarette smoking, and physical activity. Results: Of the participants, 28% were classified as living near a major road. During a median of 5 years follow-up, 403 new type 2 diabetes cases occurred. After controlling for potential confounders, proximity to a major roadway was not associated with fasting glucose at baseline, and there were no associations with changes in fasting glucose over time. No significant association with incident type 2 diabetes was found. Conclusion: This study does not support the hypothesis that long-term traffic pollution exposure may increase the risk of type 2 diabetes. Additional studies with longer follow-up periods and improved exposure estimates are needed to further investigate the hypothesized association.

Automatic road extraction in rural areas, based on the Radon transform using digital images

Manual digitizing of road maps is an expensive and time-consuming task. We present a method based on the Radon transform, which automatically extracts roads in rural areas from digital images. The proposed method iteratively detects linear segments and then generates road centerlines. The proposed method is composed of two phases: in the first, the seed segments are detected, and in the second, road widths are measured and successive detection of line segments that are candidates as road centerlines is performed. Several tests were carried out using aerial photographs (digital images) of a rural area in Brazil, and the results are presented and discussed. The quality of the extracted road centerlines was computed using the following indexes: completeness, correctness, and RMS. The values obtained show that the proposed methodology performs well.