Road Quality Research Articles

Study on the Performance of Nano-Zinc Oxide/Basalt Fiber Composite Modified Asphalt and Mixture

In order to improve the service quality of roads and resolve the problem of defects in the conventional asphalt pavement in service, this paper uses a 5.3% aluminate coupling agent to modify the surface of nano-ZnO and prepares a composite-modified asphalt with nano-ZnO and basalt fiber (BF) as modifiers. First, the basic performance of different types of asphalt was investigated by means of a rotary film oven experiment. Then, a dynamic shear rheology experiment was carried out to analyze the high-temperature anti-rutting performance of the composite-modified asphalt at different temperatures and frequencies. Then, using a bending creep stiffness test, the low-temperature properties of the composite-modified asphalt were investigated. Finally, the microstructure and modification mechanisms of the composite-modified asphalt were analyzed with scanning electron microscopy and infrared spectroscopy. The results indicate that the anti-aging performance of the nano-ZnO/BF composite-modified asphalt is significantly improved after adding fibers to the modified asphalt. The average mass loss ratio is only 0.192%. At 46 °C, the rutting coefficient of the composite-modified asphalt was increased by 62.3%. The frequency master curve is always at the highest position and continues to rise, indicating a significant improvement in the high-temperature anti-rutting performance of the composite-modified asphalt. At 24 °C, the creep stiffness modulus S value of the composite-modified asphalt increased by 24.9%; moreover, there is no obvious effect of improving low temperature, but the variation range of creep tangent slope m of the modified asphalt after aging is decreased, which further shows that the addition of a modifier can decrease the influence of aging on asphalt. Nanoparticles are uniformly dispersed in the asphalt and form a three-dimensional interconnected structure with BF, which effectively improves the overall performance of the asphalt. Nano-ZnO and fibers have weak chemical reactions in matrix asphalt, but they are physically dispersed and compatible.

Transformation of the historical heritage and spatial perception of Ilūkste

The development plan of the Upper Daugava Region (2022-2027) identifies Ilūkste as a potentially strong development centre of regional importance. The plan is designed to improve the quality of roads of regional importance infrastructure development and tourism in the Ilūkste area. This document encourages the initiation of serious cultural landscape research for Ilūkste. The scale of the existing Daugavpils development, the visibility and proximity of the city do not weaken and create strong competition for Ilūkste, but on the contrary - strengthen the revival of Ilūkste as a historic centre alongside a large-scale settlement. That means that on opposite banks of the Daugava there are two different urban spaces with different cultural and historical layers and scales. The preservation of cultural heritage is increasingly being discussed in the forums of the European Union, highlighting the values that are being lost in warfare and in the wastefulness of national economic policies. The problem of heritage conservation is also present in areas where there is no war, but where mistakes have been made due to the ineptitude of the political authorities. This is also true of the Latvian Awakening in the 1990s, when, after the occupation, "business as usual" still continued. With the collapse of collectivisation and the development of private enterprise, no attention was paid to the concepts of landscape, viewpoints, silhouettes, landmarks, climaxes, etc. The smaller the scale of the cultural landscape, the deeper the cracks of neglect that are left in the cultural landscape. The small town of Ilūkste is one example in Latvia. The loss of the intrinsic spatiality of a historic small town risks transforming not only the perception of place and people at a local level, but also at a regional and national level, thereby changing the character and uniqueness of a nation's living space. Natural and man-made elements are constantly changing, seeking to adapt. Biological processes, economic and political power, generational change, rapid technological development can all influence the development of an area. As one changes, another is subjected to change, resulting in a complete or partial transformation. This is most evident in small towns, which have long been subject to political change and the outflow of the younger generation to the metropolises. Historical space is thus also surrounded by indifference and neglect. The current municipality of Ilūkste has energetically set to work to recover the historic identity of the settlement, conscious of both the revival of the former Jesuit church and convent and the dismantling or renovation of aesthetically poor-quality buildings.

Investigation on a Vision-Based Approch For Smart Pothole Detection Using Deep learning Based on Fast CNN

The quality of road these days are important and roads always dangerous since its filled with potholes and damages which cause a lot of incident and numbers gets more increased in crowded area , this article investigates and compare the performance metrics of different object detection models that utilized the Fast CNN structure in it's backbones , Four processes make up the standard method of pothole detection: data acquisition, data pre-processing, feature extraction, and pothole classification. for the task of pothole detection. The study focuses on the evaluation of YOLOv6n, YOLOv8n, YOLOv5n, and YOLOv7 models using a dataset of road images containing pothole instances. The performance metrics analyzed include precision (P), recall (R), mean average precision at 50% IoU (mAP@.5), and mean average precision from 50% to 95% IoU (mAP@.5:.95) . The findings indicate that YOLOv8n demonstrates the highest overall performance, achieving significant precision and recall rates. These results provide valuable insights into the effectiveness of object detection models for pothole detection, contributing to the field of road maintenance and safety. The outcomes of this study can assist in the development of intelligent systems for automated pothole detection and maintenance planning

Assessing road roughness using UAV-derived dense point clouds

The quality and safety of road networks are of paramount importance in modern transportation infrastructure. Road surface conditions, particularly road roughness, significantly impact vehicular travel safety, user comfort, vehicle operating costs, and overall road infrastructure maintenance. Traditional methods for road roughness analysis, such as manual inspections or image annotation, often present limitations in terms of data completeness, efficiency, and cost-effectiveness, especially for extensive road networks. This study investigates the potential of Unmanned Aerial Vehicles (UAVs) equipped with Structure-from-Motion (SfM) derived point clouds to transform road roughness assessment. By leveraging the capabilities of UAVs, including rapid data acquisition and high-resolution imagery, and employing SfM to generate detailed point clouds, this research aims to provide a comprehensive analysis of road surface conditions. The study, conducted on a road segment within the Harran University Osmanbey campus, systematically examines road roughness at different kernel sizes: 30 cm (smaller), 50 cm (moderate), and 75 cm (larger). Through this investigation, insights are gained into how different scales of analysis influence roughness measurements. The findings highlight the potential of UAV-derived point clouds as a promising avenue for road roughness analysis, offering transportation authorities and road administrators an efficient and cost-effective means of maintaining and enhancing road networks. The integration of this technology could lead to the development of safer, more efficient, and economically sustainable road transportation systems, benefiting both road users and infrastructure managers. As research and technological advancements in UAV-based road roughness assessment continue to progress, the potential for revolutionizing road management practices becomes increasingly apparent, ultimately leading to improved road quality and enhanced travel experiences for road users.

Reflective Properties and Lighting Quality of Urban Asphalt Roads in a Full-Service Cycle: A Longitudinal Study in Zhejiang Province, China

To optimize the lighting design of urban roads in China and improve traffic safety, the present study conducted a 10-year longitudinal experiment on urban asphalt roads in Zhejiang Province, China, and analyzed variations of the road surface’s reflective properties and lighting quality with different service lengths, surface areas, and observation angles. The results showed that these roads were R2 roads with low resilience and strong directional reflection. The average luminance coefficient Q0 reached maximum and minimum at the beginning and after around one year of service, respectively. After four years of service, Q0 was about 80% of its initial value and remained stable. The specularity factor S1 reached a maximum of around two years of service. The average luminance Lav was approximately 35%, and overall luminance uniformity U0 was 31%, lower than that of R3 roads during the toughest period of the service life. If the lighting design follows the 1° observation angle r-table recommended by the specification, high Lav and low U0 occur for roads like expressways, leading to a significant increase in traffic safety risks; collector roads may suffer from insufficient Lav. Urban asphalt roads in Zhejiang Province, China, should use the R2 road standard and increase the design value of Lav by 35–45%, and high-level roads should increase the design value of U0 by 40%. The present study will provide scientific references for the design of lighting for urban roads in China, thus promoting long-term sustainable traffic safety in cities.

Analysis of pressure perception of internal roads in existing settlements based on random forest/deep learning

The quality of road space has an influential role in human psychological health. Quantifying residents' perceptions of road spatial quality and exploring the relationship between perceptions and constituent elements have become topics of interest to many parties. In this study, based on the high-resolution remote sensing images acquired by Baidu Maps, the road images of built-up settlements in Beijing in three different periods (1949-1977, 1978-1997, and 1998-2022) were semantically segmented. The large-scale rating data and subjective evaluations of residents' spatial perceptions of roads were analyzed using random forest and multiple linear regression methods. The results show that stress, a negative perception, is positively correlated with buildings and cars, and negatively correlated with vegetation, sky, and sidewalks. The composition of elements affecting residents' stress perceptions in communities of different build-up years was consistent, but the degree of influence of each element was ranked differently. This study attempts to summarize the road characteristics and residential advantages of different built-up neighborhoods, and proposes optimization strategies for upgrading road space in old neighborhoods and countermeasure suggestions for future improvement of the human living environment.

Investigation of subgrade conditions on the Airbara – Toboali road section to improve road quality

The Airbara - Toboali Road Section is a national road located in South Bangka Regency, Bangka Belitung Islands Province. Some segments of this road often experience road damage, although road repairs have been carried out several times to overcome the damage. The subgrade layer is the most important layer in the pavement structure because it functions to withstand all the loads above it. CBR (California Bearing Ratio) is penetration test used to evaluate the subgrade strength of roads and pavement. Therefore, this study aims to investigate the subgrade conditions on the Air Bara – Toboali road section in order to improve road quality. This study uses hand boring testing with 4 sampling points and field CBR testing with the DCP tool. Field CBR samples were taken as many as 30 points every 50 meters from STA 0+000 – STA 1+450. The average CBR value obtained shows that the CBR of this subgrade is in the good category (10.77%). Subgrade conditions per layer, namely at a depth of 0-2 meters the roads have almost the same soil characteristics. However, the soil depth of more than 2 meters in several locations on the road segment has a different character. The results of this investigation are expected to assist road planning so that road quality can improve.

Texture Depth Measurement using a Micro-volume Measurement Technique for Gyratory Compactor Specimens

Introduction: Road safety plays a pivotal role in transportation infrastructure, as the quality of road surfaces is a crucial factor in ensuring safe driving conditions. One of the main indicators of road quality is the Mean texture depth (MTD), which greatly affects a vehicle's traction and skid resistance. Multiple methods are available for analyzing fabric depth, with the volumetric method, known as the sand patch test and standardized under ASTM E 965 – 96, being the traditional approach. Aim: This research aims to adapt a Sand Patch test procedure to evaluate surface texture depth on laboratory specimens with a 100 mm diameter and determine the required amount of sand, both in terms of weight and volume, to conduct this test effectively. Methods: To achieve this, the relationship between the amount of sand required and the sample size was determined. Two different types of asphalt mixtures were studied Stone Mastic Asphalt (SMA) and Asphalt Concrete (AC), with five gradation limits for each. Results: In the case of the AC10 mixture, the MTD ranged from 0.60 to 1.139 mm, while in SMA 20, the MTD ranged from 1.91 to 2.574 mm. These results are consistent with previous studies, confirming the reliability of the testing methodology, even when working with limited sample areas. Conclusion: In conclusion, the study highlights the potential simplicity and cost-effectiveness of using the Sand Patch micro-volume measurement method. When employed at the initial design stage, this method can provide valuable insights into surface texture, enhancing the design process and potentially further improving road safety.

Determining criteria weights with genetic algorithms for multi-criteria decision making methods: The case of logistics performance index rankings of European Union countries

One of the most critical metrics for evaluating countries’ logistics performance is the Logistics Performance Index (LPI). Although the LPI is an effective tool, it is also an index with some concerns regarding performance evaluation. The two main concerns with LPI are assuming equal criterion weights and ignoring operational logistics performance and macroeconomic indicators. To overcome these problems, this study presents a logistics performance evaluation model in which the criteria weights are determined by GA. This study used 11 techniques to determine the logistics performances of the EU countries across 33 indicators. Employing more than one MCDM techniques enabled robustness and consistency. Median, Mean, Linear and K nearest neighbor techniques are implemented to impute the missing values in the dataset. The Linear Regression method is found as the best-performing imputation technique among other techniques for the data of this research. The performance of the GA is compared with other well-known criteria weight determination procedures namely CRITIC, Entropy and equal weight. The ranking results of the MCDM tools were integrated with the Copeland method. The genetic algorithm assigned the highest three weights to the Goods, Value of Exports, Quality of roads, and GDP per capita, indicating that these criteria play an essential role in the countries' logistics performance. The importance of these criteria is not captured by other weight sets. The correlation with the actual LPI scores is higher with Genetic algorithm compared with other weight determination techniques (CRITIC, Entropy, equal weight). Moreover, random weights are created and the results are examined. Weight simulation indicates that, some of the countries ranking are higher than the other countries, regardless of the weights of the criteria. The paper's novelty is to use the Genetic Algorithm (GA) as a criteria weight determination tool for MCDM methods. The proposed system can be used as a decision support system for evaluating the logistics performances of countries. The LPI index is published every two years, but if an automatic or semi-automatic system can be developed using the proposed approach, the logistics performance ranking of countries can be examined more frequently. This can help countries that want to rank high on the LPI ranking determine which criteria to focus on to improve their logistics performance.

Effect of SBS structure on viscosity of SBS-modified asphalt based on molecular dynamics: Insights from shearing phase morphology, adsorption and swelling mechanisms

Optimizing styrene–butadiene–styrene copolymer (SBS) design for pavement engineering is crucial for producing cost-effective SBS modifiers and improving road quality. Five types of SBS molecules were characterized using 1H NMR. The influence of SBS content and molecular structure on the viscosity and compatibility was explained by molecular mobility, shearing phase morphology, adsorption and swelling behaviors based on molecular dynamics. The results show that the viscosity contribution of SBS is determined by the SBS molecular structure and phase morphology. SBS with longer and more regular chain structure exhibits lower mobility, and a higher propensity for forming network structures, which enhances resistance to the disaggregation of polystyrene (PS) and disentanglement of polybutadiene (PB) during shear. Furthermore, the viscosity contribution of asphalt is determined by the adsorption between SBS and maltenes, as well as the competition between SBS and asphaltenes, which reduces the maltenes mobility and promotes the asphaltenes aggregation. With increasing SBS content, the adsorption strength between SBS and maltenes increases and SBS tends to form a network structure, leading to an increase in viscosity. SBS with high trans-1,4 PB content (SBS-t) exhibits the best viscosity contribution, owing to its exceptionally long and regular molecular chain. High maltenes content or a wide SBS distribution range increase the compatibility. SBS-t has the largest distribution range, resulting in the largest contact area and the best compatibility.

A comparative analysis of road and vehicle qualities as factors of road traffic carnage in Nigeria

Background and objectiveCarnage on roads is a growing concern in Nigeria. Over 27 persons, equivalent to more than 4 families, die daily from road traffic crashes. Two direct factors of a road crash are road quality and vehicle quality. To interrogate and compare both factors to road traffic accidents, the longitudinal study regressed secondary data on death tolls against road quality and vehicle quality.Materials and methodsData on the estimated number of vehicles imported into Nigeria (1992–2021) served as the indicator of vehicle quality on Nigerian roads. The longitudinal study regressed secondary data on death tolls (2013–2019) against road quality (2006–2019) and vehicle quality (1992–2021).ResultsResults showed that road quality is degenerating as well as vehicle quality in Nigeria, resulting in increase in the number of road traffic crashes and the attendant death tolls. For every 1% decrease in road quality, death tolls from road traffic crashes in Nigeria increased by 0.00642% at 5% significance, and for every decrease in vehicle quality, death tolls from road traffic crashes in Nigeria increased by 0.327% at 5% significance.ConclusionThe study recommended increased advocacy on the sanctity of life and the need for all tiers of government to prioritize policy and implementation of improving the road quality and vehicle quality to reduce road traffic crashes and save lives on Nigerian roads.

Effect of road markings and road signs quality on driving behaviour, driver’s gaze patterns and driver’s cognitive load at night-time

Night-time conditions are one of the most complex driving situations due to limited availability of visual information in the environment and limitations to the human visual system. In such conditions, road markings and road signs are the main source of information for drivers. Research has shown that road markings and road signs, if properly designed and placed, can positively impact driver behaviour and thus overall road safety. However, it is still not completely clear how different levels of road markings and road signs visibility affect drivers in night-time conditions. For this reason, we used a driving simulator to simulate night-time conditions and different levels of visibility of road markings and road signs in order to analyse the connection between the visibility of these road elements and driver behaviour and cognitive load. The results suggest that the level of road markings and road signs visibility slight increased the driving speed (about 2%), but at the same time it had a positive effect on participants’ cognitive load which was at an optimal level during high visibility. Although there was no significant difference in participants’ eye movements and the number of gazes at road markings, the percentage share of looked road signs was the highest in high visibility conditions, which suggests that the participants were in most cases timely informed and aware of the upcoming situation.

Pile Foundation Problems and Reinforcement Techniques in Highway Bridge Engineering

The construction of road and bridge pile foundations is a complex system engineering that involves many construction links. There are many common problems that can have a significant impact on the overall quality of road and bridge pile foundation construction. Therefore, it is necessary to face the quality issues of road and bridge pile foundations and take corresponding technical measures to strengthen the stability and safety of the bridge. The article discusses common pile foundation problems and reinforcement techniques in road and bridge engineering.

Contributory Factors in Traffic Congestions in the 2nd District of Albay, Philippines: Basis for Traffic Management Framework

The global concern over traffic safety conditions has escalated due to the growing number of vehicles and pedestrians. Governments are putting significant efforts into implementing systems to alleviate and reduce traffic congestion. This study aimed to identify the factors contributing to traffic congestion in the 2nd district of Albay through quantitative research. It examined traffic congestion status in terms of Data Traffic Volume, Rush Hour, Classification of Vehicles, and Road Users. The research pinpointed key contributors to congestion, including insufficient road infrastructure, high vehicle density, rapid population growth, poor public transport, and road quality. A survey questionnaire was administered to personnel from Camalig MPS, Daraga MPS, and Legazpi City Police Station, as well as Public Safety Officers from the mentioned areas. The community, representing riders and commuters in the Poblacion area, also participated. The findings revealed that traffic congestion is prevalent in the 2nd district of Albay, primarily driven by traffic volume, rush hour, vehicles, and road users. As a result, the study emphasizes the need for a standardized traffic management framework to be implemented. This framework aims to coordinate stakeholders' perceptions regarding the factors contributing to traffic congestion, serving as a guide for effective traffic management in the region.

Quality, operating properties and environmental safety of automobile road in sustainable economic development (Tomsk)

Despite positive changes in the road construction associated with the implementation of national projects aimed at a significant increase in the qualitative and quantitative indicators of the road and transport infrastructure, the resource conservation, environmental protection and safety remain relevant due to insufficient attention to them. Purpose: The analysis of the relationship between quality indicators and environmental safety of the road in the sustainable development. Approach: Balance is considered between ecological, social, economic components of the road transport infrastructure. The integrated development of road construction should serve as a functional basis of this infrastructure at all stages of the life cycle: the road design, construction, operation. Research findings: The correspondence of the actual situation in regions to modern regulatory and legal documents and economic possibilities of their implementation is considered herein. The impact of construction and operational and technological means on the environment is shown for the road life cycle. It is shown that the road construction must be oriented towards the use of innovative development that improves the quality and safety of the road transport infrastructure while addressing issues of resource conservation and environmental management.

Application of Machine Learning Techniques for Asphalt Pavement Performance Prediction

Pavement management systems (PMS) and maintaining the quality of pavement roads are crucial to human and societal well-being. However, maintaining asphalt pavement quality is complex due to various factors, such as climate change, traffic volume, material properties, and pavement age. This research aims to develop pavement condition index (PCI) models in three U.S. states (California, Hawaii, and New Mexico) using Multiple Linear Regression (MLR) and compared with four additional machine learning (ML) algorithms which are: Random Forest (R.F.), Decision Tree (D.T.), Gradient Boosting (B.G.), and Adaboost were trained. The data obtained was employed for predicting the PCI model as a function of pavement distress and traffic volume. The inputs related to pavement distress and traffic volume variables' effects: pavement age, fatigue cracking, longitudinal cracking, transverse cracking, Cumulative Equivalent Single Axle Load (ESAL), Annual Average Daily Truck Traffic (AADTT), and Annual Average Daily Traffic (AADT). According to the statistical evaluation results, all the ML models exhibited excellent prediction capabilities, as evidenced by their high coefficient of determination (R^2) values of 96.8%,96.6%,97.1%, and 97.4% and low Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Square Error values of 1.888%, 1.874%,1.830, and 1.556%, and 2.529%,2.613%,2.391%, and 2.545% and 6.348%,6.828%,5.716%, and 5.081% and 9.98%, respectively. Furthermore, the results indicate that the ML models demonstrated superior prediction accuracy compared to the (MLR) models developed under the same data.

Fine-Grained Road Quality Monitoring Using Deep Learning

Fine-Grained Road Quality Monitoring Using Deep Learning

Analysis of Technical Key Points in Road and Bridge Construction Management

With the rapid development of the country, the overall strength of the country is also increasing. With the rapid development of various industries in the country, more new technologies have been introduced and more new materials have been adopted in highway and bridge construction. At the same time, improving the quality of road and bridge construction and prolonging the service life of road and bridge engineering are also the primary tasks of construction enterprises. Therefore, in order to improve the quality of road and bridge engineering and extend its service life, it is necessary to improve the quality of road and bridge engineering on the premise of ensuring the construction focus. In the process of construction, the construction unit must effectively and reasonably choose the bridge construction technology, technological process and construction points that conform to itself, and only in this way can the quality of bridge engineering be guaranteed. In the process of road and bridge construction, the construction unit must comprehensively consider all aspects, carefully and conscientiously do every procedure, and take effective measures against various problems to ensure the construction quality, save costs and promote the development of road and bridge undertakings in China.

Construction Technology of Warm Mix Asphalt Pavement in Cold High-Altitude Areas

With the continuous development of domestic highway construction, highway civil engineering and servicelevel quality have attracted much attention. Good pavement quality and high-quality service make people feel comfortable and smooth when traveling. High-quality pavement can significantly reduce the probability of traffic accidents. At present, there is a direct relationship between pavement quality and pavement construction operations. Carrying out pavement construction operations in cold high-altitude areas requires a reasonable selection of construction equipment and methods. The application of warm-mix asphalt pavement construction technology can ensure pavement quality. Therefore, this paper analyzes the advantages of warm-mix technology, the environmental characteristics of cold high-altitude areas, and construction preparations, and discusses the construction technology of warm-mix asphalt pavement in cold high-altitude areas in detail, to improve the overall road quality of cold high-altitude areas.

A CASE STUDY OF AUTO-RICKSHAW DRIVERS IN HNAHTHIAL TOWN OF MIZORAM

In this paper, we examine the auto-rickshaw drivers in Hnahthial town of Mizoram, India by focusing their socio-economic status, issues and challenges that are being faced and the level of their job satisfaction. The study utilizes a mixed-methods approach, combining quantitative data analysis with qualitative interviews and observations from auto-rickshaw drivers, transportation authorities, and other key stakeholders. The study found that majority of the auto-rickshaw drivers are from the family of lower middle socio-economic status reflecting the fact that the driving of auto-rickshaw as the main source of livelihood is still not a gainful job. The study also found that low rate of fare with an index value of 0.8 was the most serious problem among the various problems confronted by auto-rickshaw drivers, followed by lack of auto-rickshaw stand and increasing private vehicles while lack of bad quality of road was ranked as the least significant problem with an index value of 0.51. As regard to job satisfaction, the study found that overall job satisfaction of auto-rickshaw drivers is very low. There is a higher level of dissatisfaction in terms of job security and income compared to working hours. The findings of this research shed light on the socio-economic conditions of auto-rickshaw drivers, their working conditions, income levels, and the challenges they encounter on a daily basis. The paper also explores potential solutions and strategies to address these issues and improve the livelihoods of auto-rickshaw drivers in urban Mizoram.