Road Surface Characteristics Research Articles

폭염시 도로 노면온도산출을 통한 위험등급 산정방안: 청주시를 대상으로

본 연구의 목적은 폭염 시 도로관리 우선지역 및 사고발생 위험가능지역을 산출하는 것이다. 이를 위해서 미시적 기후분석을 통해 도로노면의 구성특성과 태양복사에너지 자료에 따른 도로 노면온도 정보를 산출하였고, 여름철 노면온도에 대한 우선적 관리가 필요한 지역선별을 위한 기준을 제시하였다. 분석결과, 도로 노면온도는 지형이나 건물에 의해 발생하는 그림자유무와 높은 상관성을 나타냈고, 그림자의 비율과 표면온도의 변화량을 이용하여 4단계의 위험관리 등급을 산정하였다. 도시 외곽지역의 개방되어 있는 대형도로와 도시 내부의 낮고 평평한 형태의 공업단지 주변 소형도로에서 위험관리 등급이 높게 나타나 우선적으로 관리의 필요성을 보여주었다. 본 연구를 통해 여름철 폭염으로 인한 도로피해 대응 및 예방을 위한 관리요소들을 도출할 수 있었다.

Microwheels on Microroads: Enhanced Translation on Topographic Surfaces.

Microbot locomotion is challenging because of the reversible nature of microscale fluid flow, a limitation that can be overcome by breaking flowfield symmetry with a nearby surface. We have used this strategy with rotating wheel-shaped microbots, μwheels, that roll on surfaces leading to enhanced propulsion and fast translation speeds. Despite this, studies to date on flat surfaces show that μwheels roll inefficiently with significant slip. Taking inspiration from the mathematics of roads and wheels, here we demonstrate that μwheel velocities can be significantly enhanced by changing microroad topography. In this, we observe that periodic bumps in the road can be used to enhance the traction between μwheels and nearby walls. While continuous μwheel rotation with slip is observed on flat surfaces, a combination of rotation with slip and non-slip flip occurs when μwheels roll upon surfaces with periodic features, resulting in up to four-fold enhancement in translation velocity. The surprisingly fast rolling speed of μwheels on bumpy roads can be attributed to the hydrodynamic coupling between μwheels and road surface features, allowing non-slip rotation of entire wheels along one of their stationary edges. This road/wheel coupling can also be used to enhance μwheel sorting and separation where the gravitational potential energy barrier induced by topographic surfaces can lead to motion in only one direction and to different rolling speeds between isomeric wheels, allowing one to separate them not based on size but on symmetry.

A deep learning approach to automatic road surface monitoring and pothole detection

Anomalies in road surface not only impact road quality but also affect driver safety, mechanic structure of the vehicles, and fuel consumption. Several approaches have been proposed to automatic monitoring of the road surface condition in order to assess road roughness and to detect potholes. Some of these approaches adopt a crowdsensing perspective by using a built-in smartphone accelerometer to sense the road surface. Although the crowdsensing perspective has several advantages as ubiquitousness and low cost, it has certain sensibility to the false positives produced by man-made structures, driver actions, and road surface characteristics that cannot be considered as road anomalies. For this reason, we propose a deep learning approach that allows us (a) to automatically identify the different kinds of road surface, and (b) to automatically distinguish potholes from destabilizations produced by speed bumps or driver actions in the crowdsensing-based application context. In particular, we analyze and apply different deep learning models: convolutional neural networks, LSTM networks, and reservoir computing models. The experiments were carried out with real-world information, and the results showed a promising accuracy in solving both problems.

ABOUT THE APPROACHES TO MATHEMATICAL DESCRIPTION AND CALCULATION OF TIRE ROUAD NOISE RADIATION

Vehicles noise is a serious problem as from the point of view of impact to environment as due to the damage of vehicle's driver and passengers health. Usually in high vehicle's speed tires noise is the most significant noise source. Mathematical description of the process of sound generation from the moving source is described. Program provision for calculation of noise generation by the system "vehicle's tires – road surface" have been developed. Software is allowing to determine sound pressure level generated by vehicle's tires during vehicle movement taking to account the following factors: - velocity of vehicle movement; - characteristics of road surface; - climate characteristics (environmental temperature, rain, snow etc.); - construction characteristics of vehicle's tires; - dimensions and mass of vehicle; - engine capacity etc. Experimental data showed good coincidence with results of calculations by using of program provision.

Dynamics of Tire Crossing on a Gapped Road Surface

The safety of cars and trucks crossing gapped road surfaces can be affected by their operational speed, mass, and the tire and road surface characteristics. As part of a research on the safety of road vehicles crossing discontinuous road surfaces, the dynamic behavior of a single tire passing a gap has been examined as reported in this paper. First, the kinematics of a tire crossing the gap in the road surface is analytically formulated. The formulation has shown that the tire exhibits three distinct (single-point, two-point, and flying) modes of travel depending on its operational speed. The dynamics of the tire are larger in single-point mode that exhibits two critical velocities, which have been validated using a nonlinear arbitrary Lagrangian Eulerian method in the finite-element framework. The validated analytical model has shown that the critical velocity is mainly affected by the mass of the overburden. Introduction

Construction of Three‐Dimensional Road Surface and Application on Interaction between Vehicle and Road

The quantitative description is given to three‐dimensional micro and macro self‐similar characteristics of road surface from the perspective of fractal geometry using FBM stochastic midpoint displacement and diamond‐square algorithm in conjunction with fractal characteristics and statistical characteristics of standard pavement determined by estimation method of box‐counting dimension. The comparative analysis between reconstructed three‐dimensional road surface spectrum and theoretical road surface spectrum and correlation coefficient demonstrate the high reconstruction accuracy of fractal reconstructed road spectrum. Furthermore, the bump zone is taken as an example to reconstruct a more arbitrary 3D road model through isomorphism of special road surface with stochastic road surface model. Measurement is taken to assume the tire footprint on road surface to be a rectangle, where the pressure distribution is expressed with mean stiffness, while the contact points in the contact area are replaced with a number of springs. Two‐DOF vehicle is used as an example to analyze the difference between three‐dimensional multipoint‐and‐plane contact and traditional point contact model. Three‐dimensional road surface spectrum provides a more accurate description of the impact effect of tire on road surface, thereby laying a theoretical basis for studies on the dynamical process of interaction of vehicle‐road surface and the road friendliness.

Genetic and random search algorithms for optimising vehicle interior noise and vibration

The goal of this paper is to optimise the vehicle noise and vibration using genetic and random search algorithms (RSAs) approach. Toward this end, an experimental design was carried out to acquire the noise and vibration data using three local compact cars namely Viva, Myvi and Axia on stationary and running conditions with a variety of engine speeds transmissions. The measured noise and vibration were analysed to obtain the sound quality parameters loudness and sharpness, sound pressure level and vibration exposures in the interior vehicle cabin. Overall findings of this study indicate that the comfort level is factually influenced by factors including type of road surface, engine transmissions and vehicle design characteristics. The results also indicate that the proposed approach is reliable and can be utilised by automotive researchers to identify the optimal NVH values necessary for vehicle refinement and noise control.

Statistical model of tyre-road noise for thin layer surfacing

Noise produced from the tyre-road surface interface is one of the most important contributions to the overall traffic noise and there is an increasing requirement for predicting the tyre-road noise levels prior to road construction in the Netherlands. In practice, a model with a simple structure as well as a high accuracy is applicable in road engineering. Also, material properties are preferred to be used as input variables of the prediction model, which will facilitate the pavement design. Based on these considerations, models are developed for evaluating the tyre-road noise from the asphalt mixture compositions and road surface characteristics. They are statistical models developed from the measurements on thin layer surfacings in the Netherlands. Different regression methods, model types and input variable combinations are taken into account. The selection of the model is due to the fitness of the prediction and validation by using measurement data from in service road sections. Two models, which evaluate the tyre-road noise level from the surface characteristics and from material properties, respectively, are finally selected. By using these models, only a small number of input variables are required and reliable predictions can be provided. The models achieved in this study can be used for predicting the tyre-road noise generation in road engineering and investigating the influence of surface characteristics and material properties on tyre-road noise levels.

Concrete road surface with the use of cement concrete - selected results

Abstract The paper presents the technological concepts of the execution of modern concrete with the characteristics of road surface which have been subjected to comparative tests. Modified compositions of concrete mixtures with polymers have been tested that affect the mechanical properties and durability of the topcoat. Changes in strength properties of modified road concrete, also occurring under the influence of cyclic variable loads were investigated. Obtained results can be used to indicate the direction of further research leading to the most effective use of the advantages of polymer admixtures for concrete, mainly to improve economic indicators and reduce the negative impact of investments on the environment.

ВЗАИМНОЕ ВЛИЯНИЕ ХАРАКТЕРИСТИК ДОРОЖНОЙ ПОВЕРХНОСТИ НА КОЛЕБАНИЯ АВТОМОБИЛЯ И РЕЖИМОВ ДВИЖЕНИЯ АВТОМОБИЛЯ НА СОСТОЯНИЕ ДОРОГ

ВЗАИМНОЕ ВЛИЯНИЕ ХАРАКТЕРИСТИК ДОРОЖНОЙ ПОВЕРХНОСТИ НА КОЛЕБАНИЯ АВТОМОБИЛЯ И РЕЖИМОВ ДВИЖЕНИЯ АВТОМОБИЛЯ НА СОСТОЯНИЕ ДОРОГ

Effect of Road Surface, Vehicle, and Device Characteristics on Energy Harvesting from Bridge–Vehicle Interactions

AbstractEnergy harvesting to power sensors for structural health monitoring (SHM) has received huge attention worldwide. A number of practical aspects affecting energy harvesting and the possibility of health monitoring directly from energy harvesters is investigated here. The key idea is the amount of power received from a damaged and an undamaged structure varying and the signature of such variation can be used for SHM. For this study, a damaged bridge and an undamaged bridge are considered with harvesters located at different positions and the power harvested is accessed numerically to determine how energy harvesting can act as a damage detector and monitor. Bridge–vehicle interaction is exploited to harvest energy. For a damaged bridge, a bilinear breathing crack is considered. Variable surface roughness according to ISO 8606:1995(E) is considered such that the real values can be considered in the simulation. The possibility of a drive‐by type health monitoring using energy harvesting is highlighted and the effects of road surface on such monitoring are identified. The sensitivity of the harvester health monitoring to locations and extents of crack damage are reported. This study investigates the effects of multiple harvesters and the effects of vehicular parameters on the harvested power. Continuous harvesting over a length of the bridge is considered semianalytically. A comparison among the numerical simulations, detailed finite element analysis, and experimental results emphasizes the feasibility of the proposed method.

Road texture influence on tyre rolling resistance

Tyre performance, one of the critical factors for vehicle users, is strongly related to the road surface characteristics, most notably to the pavement texture. Phenomena that occur at the tyre/road interface affect tyre friction (skid resistance), rolling resistance, tyre wear and tyre/road noise. This article deals with relationship between surface texture and rolling resistance of light and heavy vehicle tyres. Mean profile depth (MPD) is one of the most common descriptors of road surfaces and in many studies it is correlated with rolling resistance of tyres. Results of measurements performed by the Technical University of Gdańsk show that although the correlation exists, it is not very strong and regression between MPD and rolling resistance is not linear. The key reason for this is partial enveloping of the tyre tread interacting with pavement texture. The article presents results of laboratory and road measurements of rolling resistance performed on road surfaces characterised by MPD from 0.20 up to 4.75 mm and the correlation of the rolling resistance coefficient with MPD. Certain aspects of texture enveloping and influence of this phenomenon on rolling resistance are discussed.

Application of Mixed Linear Models in the Analysis of Road Surface Features

The data were collected by researchers at the Road Research Institute, in a study investigating the impact of differentfactors on road surface strength. In this statistical analysis, we apply linear mixed models (LMMs) to clustered longitudinal data, inwhich the units of analysis (points in the road) are nested within clusters (sample of four different road segments), and repeatedmeasures of road strength in these different points are collected over time with unequally spaced time intervals. The data arebalanced – each cluster has the same number of units, which are measured at the same number of time points. Because of correlateddata and different clusters in which data could be correlated, linear regression models are not appropriate here, and therefore linearmixed models are applied.

Particulate dust emission factors from unpaved roads in the U.S.–Mexico border semi-arid region

Unpaved road dust emissions in El Paso in Texas, Las Cruces in New Mexico and Ciudad Juárez in Mexico were measured using the Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) system. PM10 (particles with diameter < 10 μm) emissions factors from unpaved roads in Ciudad Juárez, Mexico increased by a factor of five as compared to those measured in El Paso, TX and Las Cruces, NM. The highest emission factors were observed in spring. A strong exponential dependence of PM10 emissions factors on vehicle speed was observed in Ciudad Juárez, Mexico and El Paso, TX, whereas they remained constant in Las Cruces, NM reflecting differences in soil surface characteristics. The highest PM10 emissions in Las Cruces and Ciudad Juárez originated from the sideline tire, indicating the possible influence of accumulated loose soil and debris on the side of the unpaved roads. Overall, strong spatial and temporal variability of PM10 emission factors were computed in the Paso del Norte region, reflecting differences in road surface and vehicle traffic characteristics and further underscored the need for high spatiotemporal resolution of emission inventories to accurately identify the most susceptible unpaved roads and control their burden on particulate pollution.

Automatic reconstruction of road surface features by using terrestrial mobile lidar

Abstract As urban roads expand over time, road surface features become more complicated and critical to driving safety. Constructing a database of road surface features through an automatic process is particularly crucial when these features are applied to the fields of facility maintenance, autonomous vehicle assistance, 3D cyber city construction, and navigation-information renewal. This paper proposes a fully automatic approach for reconstructing road surface features based on the terrestrial mobile light detection and ranging (lidar) technique. Analysis steps were developed and an experiment was performed using a real lidar data set. The results indicated that the proposed road surface reconstruction method is feasible and that the classification indices, correctness and completeness, were both higher than 90%. Finally, the uncertainty associated with each analysis stage was explicitly assessed through an error budget analysis. This can provide a guideline for practical applications and further system optimization.

Influence of Road Surface Characteristics on Tire–Road Noise for Thin-Layer Surfacings

AbstractThis study investigates the influence of different surface characteristics on tire–road noise of thin-layer road surfacings by a statistical modeling method. The surface characteristics considered are surface texture and sound absorption. Correlation analysis and multivariate linear regression are performed to detect the combined effect of surface texture and sound absorption on tire–road noise levels. The texture is characterized by mean profile depth as well as texture level on an octave band of wavelengths, while the sound absorption is described by the absorption coefficients on the frequency spectrum as well as by the maximum absorption coefficient only. In the regression, principal component regression is used to reduce the multicollinearity between the explanatory variables. The influence of surface characteristics of thin layer surfacing on tire–road noise is observed from the regression results and the correlation analysis.

Study of road surface characteristics in frequency domain using micro-optical 3-D camera

A number of methods are used to assess the road surface characteristics, in terms of its roughness, skid resistance, texture etc. In the present work, three-dimensional (3-D) road profile data of asphalt pavements, captured by a micro-optical 3-D measuring device (covering an area of about 26 mm × 20 mm), is used to study the road surface characteristics. Analysis is performed in frequency domain to extract information on both microtexture and macrotexture from the same source data collected by the equipment. The surface parameters derived from 3-D measurement are compared with conventional parameters gathered by standard methods namely, sand patch, pendulum tester, and sideway force coefficient measurement. The proposed surface parameters show a good correspondence with the results obtained by the conventional methods. Thus, the method presented in the paper seems to have a potential for fast and automated evaluation of functional characteristics of pavement surface.

Mapping road surface features using single-camera images acquired by a mobile mapping system

Mapping road surface features, such as manholes, traffic markings, and cracks, is an essential task for transportation facility management. Although, these features can be rapidly surveyed using the latest mobile mapping techniques, a sophisticated sensor system with a complicated post-processing procedure is usually required. In this study, an efficient framework for modeling road surface features is proposed using a single camera system installed on a moving platform. First, the road surface images along a route of interest are acquired and potential objects are identified based on their shapes and recorded spectra in the images. Then, the contour pixels of the identified objects are extracted by the Canny edge detection technique. Finally, the 3D coordinates of the detected features in object space are obtained by integrating the profile-image technique and the instantaneous exterior orientation parameters of the platform. Based on the numerical results from a case study, it has been demonstrated that a fully automatic and reliable extraction of road surface features can be easily achieved by implementing the proposed approach. Consequently, the modeling of road surface features, which essentially contributes to the management of transportation facilities, can be executed in a cost-efficient manner.

Understanding the Role of Urban Road Surface Characteristics in influencing Stormwater Quality

Urban road surfaces are one of the most important stormwater pollution sources. Asphalt and concrete road surfaces are typical road types in China and have different characteristics such as roughness, textures and infiltration rates. This could lead to differences of collecting and retaining pollutants. In this context, designing stormwater treatment for different road surfaces respectively is crucial to effectively minimize the stormwater deterioration. This closely depends on an in-depth understanding of stormwater quality characteristics on urban road surfaces. This research study investigated the stormwater quality characteristics on typical asphalt and concrete surfaces. The research outcomes show that road surface characteristics could play a more important role in influencing the resulting stormwater runoff quality than rainfall characteristics. Additionally, asphalt surface due to the relatively rough nature could play a more important role in influencing the overall pollutant export characteristics from urban road surfaces. It is also noted that there are notable differences in pollutant wash-off processes on different surfaces, where the wash-off process on asphalt surfaces tends to be a transport limiting process, while the wash-off process on concrete surfaces tends to be a source limiting process. These results can contribute to stormwater treatment design enhancement for urban roads such as treatment placement, rainfall event selection and water quality estimation.

Influence of changes in surface layer properties on tire/pavement noise

This paper investigates changes in tire/pavement noise caused by variations in the road surface characteristics. This research is based on the analysis of noise and surface characteristics collected from sections with 25 mm thickness thin layer surfacings in the Netherlands. Investigations are first performed on the measured noise levels in 1/3rd octave bands, texture levels and the sound absorption curves. The one-way analysis of variance is employed to test the changes of noise caused by variations of the pavement surface characteristics. It is found that the significant differences in the noise levels between road surfaces mainly appear at frequencies higher than 1000 Hz, and they are considered to be related to surface layer properties. Multivariate linear regression analysis is performed for describing the relationship between the noise level changes and the variations of surface characteristics. By using the partial least square (PLS) regression, the combined effect of texture and sound absorption coefficients on different spectral bands is displayed. From the regression results, it can be inferred that the sound absorption variations at 1000 and 1250 Hz are important factors influencing noise reduction of thin layer surfacings. The founding provides information for designing the noise reducing thin layer surfacings.