Road Surface Type Research Articles

Vehicle Body Vibration and Noise Impact on Driver and Passengers Analysis: The Case of the 29-Seat Thaco Garden TB79s Bus

Noise, Vibration, and Harshness (NVH) are critical factors influencing the comfort and satisfaction of vehicle occupants. NVH encompasses the sound levels generated during vehicle operation, the vibrations transmitted through the vehicle structure, and the perceived harshness of the ride quality. This study focuses on the NVH analysis of the Thaco Garden TB79S, a 29-seat passenger vehicle. The Finite Element Method (FEM) is applied to simulate the impact on the vehicle as it traverses two types of road surfaces, characteristic of Vietnam: rumble strips with varying frequencies and uneven roads with random excitation. The results reveal that the Sound Pressure Level (SPL) is within the frequency range from 0 to 200 Hz while the vehicle navigates on rumble strips. Further analysis of the vehicle's body and the air mass within the cabin identifies a resonance phenomenon at the driver's ear location at 176 Hz, resulting in a maximum SPL of 166.92 dB. Additionally, the study examines the noise formation within the cabin during a 25-second period as the vehicle travels over random road surfaces. The maximum sound pressure at the driver's position reaches 0.24 psi, with the SPL fluctuating primarily between 130 and 155 dB.

Ride Comfort Evaluation of an Motorbike with Random Excitation by a Multi Body Dynamic Model

Abstract An motorbike is designed with full technical specifications regarding size and weight distributed on the front and rear axles of the vehicle. The wheel is connected to the vehicle body frame through a suspension system including linkage, spring, and shock absorber elements. The designed suspension system specifications play a very important role in ensuring the vehicle’s ride comfort, safety and road holding ability. To ensure technical requirements, the suspension system is designed with the spring and damper parameters selected as reality. The ride comfort greatly affects the quality of the vehicle’s design and the health safety of people using the vehicle. This paper focuses on the ride comfort of an electric motorbike. The assessment of ride comfort is analyzed by a Multi-Body Dynamic (MBD) model with 4 degrees of freedom (4DOF) subjected under the random excitation, according to ISO 8608 standard. The simulation is performed with three random types of road profile, class A, class B, class C. The velocity is in the range of from 10 ÷ 80 (km/h), at each value of velocity the Root Mean Square (RMS) index of the acceleration in the time domain is determined. The acceleration index includes to frequency weighting according to ISO 2631:1-1997 standard is used to evaluate the ride comfort. The MBD model in 3-dimensional (3D), including wheels in contact with the road surface, linkage bars and suspension systems linked to the vehicle frame through linkage joints, is employed. The obtained results show that, with the same v value, when the vehicle moves on road surface A class, the ride comfort is always smaller than road surface B class and C class. Considering the same type of road surface, as v increases, the ride comfort index increases, leading to a decrease in comfort and an increase in suspension working space requirement.

Mapping National‐Scale Road Surface Types Using Multisource Open Data and Deep Learning Model

ABSTRACTIdentifying road surface type (e.g., paved and unpaved) is crucial for pavement maintenance, transportation management, and road network accessibility research. Existing approaches relying on vehicle‐mounted devices or remote sensing data are have limitation for large‐scale road networks. This study proposes a novel approach to identify national‐scale road surface type using multiple open geospatial datasets and machine learning models. Specifically, 16 input variables were designed based on these datasets (including OpenStreetMap, GDP, population, building height, and land cover). Nigeria and Cameroon were selected as study areas. A substantial dataset, auto‐extracting road surface tags from OpenSreetMap, was used to train a model. The trained model predicted road surface types across the two study areas. Result indicated: (1) Most of the input variables positively impact the output variable, with “road class” being the most influential; (2) The proposed approach with deep learning model‐TabNet performs the best, with an overall accuracy above 85%; and (3) More than 83% of roads in the two African countries are unpaved, with paved roads concentrated in backbone roads and southern provinces. This approach has been validated and offers valuable insights for local authorities aiming to enhance road infrastructure.

Rolling resistance on concrete pavements in The Netherlands

In an effort to reduce fuel consumption and CO2, a measurement program initiated by Rijkswaterstaat and province Gelderland was conducted in 2013 to investigate the variation in rolling resistance of passenger cars tyres on different asphalt road surface types on the Dutch main roads (highways and provincial roads). Complementary to the rolling resistance measurements also texture measurements were performed. In addition to this program rolling resistance and texture measurements have been performed on some concrete road sections for the Cement&BetonCentrum. In total 8 concrete road sections were selected and measured. The measurements were a joint effort by M+P and TU-Gdansk. All the concrete road sections were measured on April 2013. The rolling resistance and texture were measured simultaneously. A temperature correction based on the tyre wall side temperature was applied to all rolling resistance coefficients. Two types of concrete road surfaces were measured: brushed concrete (1 road section) and exposed aggregate concrete (7 road sections of different ages: from 8 to 22 years old pavements!). The difference in average rolling resistance coefficient between brushed concrete and exposed aggregate concrete is 0.9 ± 0.4 kg/t (or 10 ± 4 %). This is a significant difference.

StreetSurfaceVis: a dataset of crowdsourced street-level imagery annotated by road surface type and quality

Road unevenness significantly impacts the safety and comfort of traffic participants, especially vulnerable groups such as cyclists and wheelchair users. To train models for comprehensive road surface assessments, we introduce StreetSurfaceVis, a novel dataset comprising 9,122 street-level images mostly from Germany collected from a crowdsourcing platform and manually annotated by road surface type and quality. By crafting a heterogeneous dataset, we aim to enable robust models that maintain high accuracy across diverse image sources. As the frequency distribution of road surface types and qualities is highly imbalanced, we propose a sampling strategy incorporating various external label prediction resources to ensure sufficient images per class while reducing manual annotation. More precisely, we estimate the impact of (1) enriching the image data with OpenStreetMap tags, (2) iterative training and application of a custom surface type classification model, (3) amplifying underrepresented classes through prompt-based classification with GPT-4o and (4) similarity search using image embeddings. Combining these strategies effectively reduces manual annotation workload while ensuring sufficient class representation.

Analysing the impact of electric kick-scooters on drivers: vibration and frequency transmission during the ride on different types of urban pavements

The purpose of this research is to determine the vertical vibration and frequency spectrum transmitted to the rider by electric scooters travelling on different types of road surfaces. Vibration analysis involves the measurement of vibration levels of e-scooter elements, accompanied by the analysis of the Fourier Transform Spectrum and using a t-sample measurement design and a one-sample statistical method. Approach in the research allows overall driver comfort to be assessed through frequency and vibration analysis, considering vibrations received by the hands and the whole body. In addition, the natural frequencies of the electric scooter components and their stability are being investigated to assess vibration transformation. The study includes an assessment of ride comfort and considers potential health implications. The results obtained facilitate the identification of critical risks associated with vertical vibration frequencies transmitted to individuals when riding electric kick-scooters in urban areas with different types of pavements.

Influence of road surface type on the magnetic susceptibility and elemental composition of road dust

The aim of the study was to determine the effect of the type of road surface (asphalt and concrete) and the presence of noise barriers (acoustic screens) on the magnetic susceptibility and chemical composition of road dust collected from national roads and motorways in central and southern Poland. Four roads with asphalt surfaces and four with concrete surfaces were selected for the study. Samples were taken at three control points: in the space between noise barriers, in the space without barriers and at road exits. Magnetic susceptibility measurements and elemental composition analysis (using an energy dispersive X-ray fluorescence spectrometer) were carried out. The results showed high variability with no clear differences between samples taken from asphalt and concrete roads. Magnetic susceptibility values were higher for road dust taken from asphalt pavements near noise barriers and motorway exits, while for open space samples the susceptibility values were about 1.3 times higher for dust from concrete pavements. A similar relationship was observed for the elemental composition. The results showed no clear differences between samples taken from asphalt and concrete roads. The location of the sampling point had a greater influence on the results: the surface of noise barriers, open spaces or motorway exits. Calculated enrichment factors indicated an extremely high enrichment of dust in elements such as Cr, Cu and Zn, a very high enrichment in Pb only for dust collected at motorway exits, and a significant and moderate enrichment in other elements.

Influence of Shock Absorber on Electric Axle Vibration in Semi-Trailer

This article describes the results of a study of the effect of a shock absorber on the vibration of an electric axle in a semi-trailer. The dynamic characteristics of three shock absorbers from different manufacturers were determined. They were then installed on the electric axle of a semi-trailer equipped with a measuring apparatus. Test runs were carried out on two types of road surface - a test track with a defined profile and a local road. Each run was repeated for a fully loaded and an empty semi-trailer. These tests were designed to determine the values of the dynamic parameters of the electric axle during operation of the semi-trailer depending on the shock absorber used.

Optimized road noise asphalt pavements - The types of noise-reducing road surfaces

The noise has long been recognized as a stress factor for humans. A high level of noise has many negative influences on health such as: difficulty to concentrate, stress, health issues for the ears, and also has a damaging effect on the cardiovascular and endocrine systems. Road traffic is main source of total noise, especially in conurbations. In order to effectively reduce noise emissions, surface courses can be installed as road surfaces that generate particularly little noise in interaction with the vehicle tire. This paper delas with different types of noise-reducing road surfaces.

Assessment of Semi-Flexible Pavement Using Styrene-Butadiene Emulsion Modified Cement Grout

Semi-flexible pavement (SFP) is a type of road surface that combines open-graded asphalt concrete with cement grout for wearing courses containing 18 to 28% air voids. This study investigates the effectiveness of two types of cement grouts using modified styrene-butadiene emulsions, Sika Latex and Sika Latex TH, with varying amounts ranging from 4.5% to 7.5% and 7.5% to 9%, respectively. The goal of the paper is to determine the appropriated type of styrene-butadiene emulsion type for SFP. To create the SFP, the selected grout and Vinkems Asphalsol grout with a water-cement ratio of 0.45 were poured into the asphalt structure, resulting in an SFP with 22.8% air voids. Additionally, several experiments were conducted to evaluate the effectiveness of SFP. These experiments included the Marshall stability test, indirect tensile strength test, and resilient modulus test. The study results showed that Sika Latex 6.5% and Sika Latex TH 9% had good properties for use in SFP.

Contribution of congested traffic flow condition to air pollution at intersections in Addis Ababa, Ethiopia

Contribution of congested traffic flow condition to air pollution at intersections in Addis Ababa, Ethiopia

Study of Concrete Pavement at Chichpalli, Jambharla

Concrete pavement is a type of road surface made from a mixture of cement, water, and aggregates such as sand and gravel. It is a durable and long-lasting option for roads, highways, and parking lots due to its strength and resistance to wear and tear. The process of constructing concrete pavement involves preparing the subgrade, placing a base layer of aggregate material, and then pouring and finishing the concrete mixture on top. The concrete is typically reinforced with steel bars or fibers to improve its tensile strength and prevent cracking. Once the concrete pavement has been poured and cured, it provides a smooth and even surface for vehicles to travel on. It is also easy to maintain and repair, as damaged sections can be easily replaced or patched. Concrete pavement is a popular choice for infrastructure projects due to its durability, longevity, and low maintenance requirements

Mapping Road Surface Type of Kenya Using OpenStreetMap and High-resolution Google Satellite Imagery

Identifying road surface types (paved or unpaved) can ensure road vehicle safety, reduce energy consumption, and promote economic development. Existing studies identified road surface types by using sensors mounted on mobile devices and high-resolution satellite images that are not openly accessible, which makes it difficult to apply them to large-scale (e.g., national or regional) study areas. Addressing this issue, this study developed a dataset of road surface types (paved and unpaved) for the national road network of Kenya, containing 1,267,818 road segments classified as paved or unpaved. To accomplish this, this study proposes a method that integrates crowdsourced geographic data (OpenStreetMap) and Google satellite imagery to identify road surface types. The accuracy, recall, and F1 score of the method were all above 0.94, validating the effectiveness of the method. The data sources of the method are freely available, and the method may be applied to other countries and regions. The dataset developed based on the method can provide data support and decision support for local governments to improve road infrastructure.

COST AND TIME ANALYSIS OF DRAINAGE WORKS USING CONVENTIONAL RIVERSTONE METHOD AND PRECAST U-DITCH METHOD

Road drainage is part of the infrastructure required for roads. This infrastructure is designed to drain water from the surface of the road to its final disposal. In general terms, drainage is a series of structures designed to reduce and remove excess water from an area or land to allow the land to function optimally. There are two types of road drainage systems, surface and subsurface. Surface drainage systems are generally open or closed channels. The method used in this research is quantitative method, where this method explains a process of seeking knowledge using data in the form of numbers as a means of analysing information about the things is desired to know about a situation that becomes the object of study and then analysed with the help of Microsoft Excel 2013 and Microsoft Word 2013 software. The comparative analysis results of the cost and time for implementation of drainage works using the conventional river stone method over a length of 192 metres requires 55 working days at a cost of Rp 123,617,000.0, while the precast U-ditch method over a length of 174 metres requires 48 working days at a cost of Rp 78,292,000.0. Where the implementation of the conventional method turns out to be 14% longer than using the precast method. The results of the analysis of the cost per metre of drainage works using the conventional river stone method and the precast u-ditch method obtained the results, which are drainage works using the conventional river stone method amounting to Rp 6,438,385 while the work using the precast u-ditch method is Rp 4,449,540, with the difference between the two methods amounting to Rp 1,988,845. Where the use of the precast method is 30% lower than the conventional method.

Leaching characteristics of metals and Polycyclic Aromatic Hydrocarbons (PAHs) from asphalt paving materials

Leaching characteristics of metals and Polycyclic Aromatic Hydrocarbons (PAHs) from asphalt paving materials

Statistical modeling of cargo securing on selected military trucks and road surfaces

The development of new technologies (e.g., three-axial accelerometers) and their implementation to the armed forces made it possible to rather easily obtain data on transportation with regard to cargo securing. It is, however, crucial to evaluate the data, and identify the factors important for the selection of an appropriate cargo securing system. Particular attention should be paid to the transportation on low-quality roads, or possibly in the terrain as it can be expected that the cargo (as well as the vehicle and the driver) is subjected to greater shocks. Data obtained from the military transport experiment have been processed using advanced statistical methods (a contaminated probability distribution, methods of statistical comparison, and an analysis of variance). The transportation data from the use of two military trucks on three different road surfaces has been compared. The results show, in which axes there are statistically significant differences in terms of the frequency of exceeding normatively determined acceleration coefficient values in relation to the road surface type and the vehicle type. Further results are based on the modeling of acceleration coefficients using a contaminated log-normal distribution, where the distribution of acceleration coefficient values is contaminated by outliers resulting from sudden changes in the transport conditions.

Experimental investigations of steady-state deceleration parameters of L6 category vehicles

At the moment, the authors have not been able to find updated databases that allow the expert to choose the braking parameters of vehicles of category L6, which are as close as possible to the road situation that preceded the accident, when conducting road traffic (auto-technical) examinations. Within the framework of this work, the authors investigated the nature of changes in the steady-state deceleration of vehicles. Based on the obtained results of experiments on the category of vehicles L6, the researchers have determined the data on the braking distance and the average value of deceleration during braking on different types of road surface. Keywords road transport expertise, traffic safety, deceleration, L6 vehicle category

ACOUSTIC POLLUTION OF CITIES AND ITS IMPACT ON HUMAN LIFE ACTIVITIES

The results of acoustic measurements and sociological studies indicate that the main source of acoustic pollution in cities is motor vehicles. About one in two city residents suffers from the noise it generates. Imperfect legislative and regulatory framework, lack of economic instruments to regulate acceptable levels of noise is the reason for the growth of acoustic pollution in cities. The most investigated is industrial noise, while the problem of urban street noise is less studied. It is very difficult to study street noise because this type of noise can originate from a large number of sources. The aim of the study was the measurement of noise pollution and its mode within two cities of different countries. In particular, it is the review of the processes of noise pollution impact on human health and the environment, analysis of the current state of noise pollution in urbanised territories, as well as the identification of modern mechanisms for solving noise pollution issues in urbanised territories. Research methods: field measurements of acoustic pollution levels, analysis, statistical processing of research results, generalisation. Measurements of the maximum level of sound were carried out with the help of FLUSET-965 device. Measurements were conducted according to the standard methodology. The dynamics of noise pollution in the streets of Holosievsky district of Kyiv in comparison with the streets of Cologne, Germany allows us to understand that the type of road surface, traffic intensity, organisation and composition of traffic flow has a significant impact on the level of noise pollution. The methods of calculation of the expected noise level of road transport can be taken as a basis for the selection of building-acoustic measures for protection of residential premises and public buildings from transport noise.

Automatic Identification and Evaluation of Building Clusters for Optimal District Heating Networks Phasing

Considering future city changes when designing district heating networks can be tedious. This paper tackles this problem by automatically identifying potential future building clusters connections, and evaluating relevant financial and planning criteria. The methodology uses open GIS data for cluster identification and building heat demand estimation, and thermal-hydraulic models for simulating the network. On a neighbourhood scale, area characteristics such as total heat demand, distance to source, and road surface type mainly affect the decision of where to expand the network to. However, on a street scale, the sizing and location of the initial network mainly affect the network’s phasing.

Smart monitoring of road pavement deformations from UAV images by using machine learning

Road pavement deformation monitoring is considered the main task for maintenance purposes, especially potholes and cracks, which are the most common types of road deformation surfaces. In order to make pavement inspections more effective, new types of remote sensing data that do not damage the pavement are being used more and more to find pavement distress. This article presents a proposed approach for extracting surface cracks from unmanned aerial vehicle (UAV) images using machine learning, focusing on the data pre-treatment processes. The objective of this study is to evaluate the effectiveness of decision tree classification (DT) in detecting cracks. The performance of the models is also evaluated. The performance evaluation approach is predicated on two primary criteria: model validation and testing. Also, the extent of the impact of post-classification operations, edge detection technology, and morphological processes on crack identification as well as classification accuracy, the digital orthomosaic was generated by the use of a technique commonly referred to as backward projection. To achieve this, the study uses a fusion of gray-level co-occurrence matrix (GLCM) attribute data and RGB images. Cracks are discovered using a classification tree (CT)-based classification approach with an overall classification rate of 86%. Ultimately, morphological processes using the closed image that was formed had a commendable level of accuracy, with an overall classification rate of 96%. The Canny edge detection algorithm has demonstrated its efficacy as a preferred method for detecting cracks from UAV images, providing invaluable decision support for actual road maintenance.