Road Sections Research Articles

Studi Kinerja Ruas Jalan Di Sekitar Masjid Terapung BJ. Habibie Kota Parepare

Construction of the BJ Habibie Floating Mosque influences the volume and system of traffic movement, the existence of high efficiency has an impact on increased traffic flow and demands the provision of a road network. The aim of this research is to identify the performance of roads and intersections and also to determine the impact on traffic due to the construction of the BJ. Habibie Floating Mosque by using the MKJI 1997 analysis. The results showed that the heaviest traffic flow on the Mattirotasi road section occurred on Saturday at 16.00 until 17.00 WITA with a traffic volume of 220.1 pcu/hour, a v/c ratio of 0.11 and Level of Service A with average vehicle speed 28.77 km/hour. Massepe road section occurred on Sunday at 16.00 until 17.00 with a volume of 943.49 pcu/hour, a v/c ratio of 0.30 and Level of Service B with an average speed of 28.06 km/hour.

Analysis of Traffic Performance and Passenger Car Equivalent Value in Tangerang – Merak Toll Road Section

Economic growth involves massive movement of logistics, where goods transported by land become the main choice by supplier. One of them being the main access for connecting Java and Sumatera is the Tangerang – Merak toll road. An increase in traffic volume occurs every year, followed by additional problems such as congestion which obviously affects traffic performance. Given this reason, it is necessary to evaluate traffic performance through parameter assessments, which are the degree of saturation and travel speed. This research was carried out on the Tangerang - Merak toll road section KM 32,300 to KM 35,500 towards Jakarta for one week using traffic CCTV recordings, then selected on 17 April 2024. The calculation results obtained for each average weighted value for the degree of saturation (Ds) at 0.36 and average of the Space Mean Speed is at 33.08 kph. Based on traffic performance analysis, the volume parameter does not indicate a problem, and is included in the LOS A category. However, the travel speed parameter shows an issue and included in the LOS F category. This will be the focus problem within the scope of the research. On the other side, traffic composition which includes variations in the number of vehicles per time and type of vehicle. Given this kind of variation, a Passenger Car Unit value is needed that can equalize the existing different vehicle types into a uniform standard, including who commit over dimensional violations. Where the value of passenger car equivalent of an over-dimensional vehicle is changing, it is necessary to re-calibrate the emp value. Researchers used the Volume Delay Function formula to calculate travel time, then explore a combination of emp values using the dynamic programming method by comparing survey travel time with the simulation one. The difference between the PKJI standard value and the calibrated pce value proves the problem of these vehicles commit over dimension violations on the Tangerang – Merak toll road. For this reason, it is hoped that this research which evaluate traffic performance, travel time and passenger car equivalent values, can be used as a basis for further policy making to improve the performance of the Tangerang – Merak toll road.

Prediction model of factors causing traffic accidents on rural arterial roads: A binary logistic regression approach

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

Determination of Motorcycle Equivalent Unit and Road Capacity: A Case Study of Selected Road Sections of Kathmandu Valley

The research focused on road congestion in Kathmandu Valley, Nepal, caused by the prevalence of small motorized vehicles, especially motorcycles. The objective of the study was to quantify the impact of different vehicle classes on congestion by calculating Motorcycle Equivalent Units (MEU) and determining roadway capacity using speed and effective space parameters. The field data collected over two locations in Kathmandu Valley were analyzed using Speed Estimation from Video Data (SEV) software that revealed a strong correlation between vehicle speed and effective space, represented by a quadratic non-linear model. MEU values were determined for different vehicle classes, and fundamental speed-flow-density relationships were used to calculate roadway capacity. Vehicles like motorcycles, standard cars, big cars, utility, minibusses, buses, light commercial vehicles, two/three-axle trucks, and multi-axle trucks had MEU values of 1, 3.32, 4.91, 4.65, 9.22, 12.22, 6.72, 13.57 and 18.04 respectively. The study indicated peak capacities during the evening hours on specific road sections. For instance, the Gatthaghar-Kaushaltar and Balkumari-Gwarko sections reached their maximum capacities at 12,335 and 20,589 (motorcycles per hour per direction), respectively. The study emphasized the significant influence of speed on effective space and roadway capacity, suggesting further exploration of additional factors like driver characteristics, gender, age, income, road geometry, and level of service using MEU, along with the potential for developing a motorcycle simulation model in Kathmandu valley.

Lokalizacja wlotów kratek ściekowych w celu zapewnienia skutecznego odwodnienia ulic w procesie projektowania ulic i planów nawierzchni w Bułgarii

This study analyses the existing requirements and standards for determining the locations of grate inlets on streets in Bulgaria. Effective drainage in street design is essential for managing stormwater runoff and preventing urban areas from flooding during heavy rains. To choose optimal locations of grate inlets plays a crucial role in this process. Solving this task is related with designing street slopes in grading plans and designing sewer systems. This article presents an approach, based on successful practices used in the USA and Australia, by proposing a hydraulic based procedure for locating grate inlets in the design process. The technique is adopted to all Bulgarian requirements and standards. As a main criterion it is suggested to use the maximum allowable water spread on the pavement of the traffic lanes. The proposed method considers various factors, such as longitudinal and cross slope, size of grate inlet, design frequency period, intercepted and bypass flow. It starts with determination of the grate inlet locations on continuous grade, then incorporates the specific sag points in vertical curves and intersections. It can be used in the process of designing streets and their grading plans to optimize the drainage efficiency of streets in Bulgaria. It is hydraulic reasoned, very flexible, and easy to apply for different street sections with different features. Implementing this approach can solve the problem of unclarity in locating grate inlets in Bulgaria. Also, the presented procedure could be used as a base to fill gaps in the existing Bulgarian regulations and manuals, related to the drainage of streets in urban areas.

Integrated Strategy in Road Assesment for Tameroddo-Majene City Boundary Road Section Preservation

Tameroddo – Majene City boundary road section is a national road in West Sulawesi, a road connecting South Sulawesi and Central Sulawesi provinces. Its existence is essential for increasing accessability and mobility between regions, for it does not only support economic growth in the West Sulawesi Province, but it also has some positive impacts on socioeconomic development for surrounding areas. Traffic volume, overload, and rainfall are factors that accelerate intensity of road surface irregularities. An analysis of road pavement conditions is, therefore, required to provide existing data for road preservation, to ensure its optimum function in accordance with planned durability. This research is aimed at providing assessment results of the road section conditions, and to compare the results between IRI and PCI measures, as well as to provide an overview or description of the road section conditions. This can, thereafter, be used as an important database for a better planning and implementation. Road assessment had been conducted using an integrated method, by IRI measure performed by using ‘The Hawkeye’ vehicle equipped with high precision laser profilers and accelerometers, DMI, and high-speed cameras along with GPS, incorporating Dinamic Time Warping (DTW) technique, to automatically detect and classifies road irregularities on paved roads. This method, however, followed by manual inspection (or subjective measures). Survey result shows that based on IRI method, ‘fair’ condition reaches 67%, and lightly damaged reaches 33%. While based on PCI method, ‘good’ (equivalent with ‘fair’) condition reaches 66%, and ‘bad’ condition (or equivalent with ‘lightly damaged’) condition reaches 34%. This means that the study found some differences, even though it was only a little. Based on analysis result, amongst total lenght of the road lane had been under assesment (81,8 km), 74,4 km is of ‘fair’ condition, thus it requires a routine maintenance, while the rest 8,4 km is of ‘lightly damaged’ and it requires a regular maintenance.

Traffic Anomaly Detection based on Spatio-Temporal Hypergraph Convolution Neural Networks

Traffic Anomaly Detection (TAD) is an important and difficult task in Intelligent Transportation Systems (ITS) . Traffic anomaly events are sparse in both spatial and temporal spaces, posing a challenge to the performance of model. Moreover, a single traffic anomaly event can impact multiple road sections in the neighborhood, further undermining the accuracy of TAD. In this paper, we propose a new TAD method based on spatio-temporal hypergraph convolutional neural network. Specifically, we adopt a spatial–temporal augmentation approach for traffic data. This will enhance the performance of detecting sparse anomalies. Meanwhile, we introduce a hypergraph learning method to model the road network. This could capture the spreading features of anomalies for better detection results. Additionally, we design a dynamic hypergraph construction method to extract the evolving relationships of road segments. The proposed model evaluation on the Beijing (SE-BJ) dataset for TAD reveals superior performance compared to state-of-the-art ones.

Identifying emerging hot spots of road traffic injury severity using spatiotemporal methods: longitudinal analyses on major roads in Ghana from 2005 to 2020

BackgroundAlthough road traffic injuries and deaths have decreased globally, there is substantial national and sub-national heterogeneity, particularly in low- and middle-income countries (LMICs). Ghana is one of few countries in Africa collecting comprehensive, spatially detailed data on motor vehicle collisions (MVCs). This data is a critical step towards improving roadway safety, as accurate and reliable information is essential for devising targeted countermeasures.MethodsHere, we analyze 16 years of police-report data using emerging hot spot analysis in ArcGIS to identify hot spots with trends of increasing injury severity (a weighted composite measure of MVCs, minor injuries, severe injuries, and deaths), and counts of injuries, severe injuries, and deaths along major roads in urban and rural areas of Ghana.ResultsWe find injury severity index sums and minor injury counts are significantly decreasing over time in Ghana while severe injury and death counts are not, indicating the latter should be the focus for road safety efforts. We identify new, consecutive, intensifying, and persistent hot spots on 2.65% of urban roads and 4.37% of rural roads. Hot spots are intensifying in terms of severity and frequency on major roads in rural areas.ConclusionsA few key road sections, particularly in rural areas, show elevated levels of road traffic injury severity, warranting targeted interventions. Our method for evaluating spatiotemporal trends in MVC, road traffic injuries, and deaths in a LMIC includes sufficient detail for replication and adaptation in other countries, which is useful for targeting countermeasures and tracking progress.

Exploring road safety using alignment perspective features in real driving images: A case study on mountain freeways.

While driving, drivers frequently adapt their driving behaviors according to their perception of the road's alignment features. However, traditional two-dimensional alignment methods lack the ability to capture these features from the driver's perspective. This study introduces a novel method for road alignment recognition, employing image recognition technology to extract alignment perspective features, namely alignment perspective skewness (APS) and alignment perspective kurtosis (APK), from in-real driving images. Subsequently, the K-means clustering algorithm is utilized for road segment classification based on APS and APK indicators. Various sliding step length for clustering are employed, with step length ranging from 100m to 400m. Furthermore, the accident rates for different segment clusters are analyzed to explore the relationship between alignment perspective features and traffic safety. A 150 km mountain road section of the Erlianhaote-Guangzhou freewway from Huaiji to Sihui is selected as a case study. The results demonstrate that using alignment perspective features as classification criteria produces favorable clustering outcomes, with superior clustering performance achieved using shorter segment lengths and fewer cluster centers. The road segment classification based on alignment perspective features reveals notable differences in accident rates across categories; while traditional two-dimensional parameters-based classification methods fail to capture these differences. The most significant differences in accident rates across categories are observed with segment length of 100m, with the significance gradually diminishing as segment length increases and disappearing entirely when the length exceeds 300m. These findings validate the reliability of using alignment perspective features (APS and APK) for road alignment classification and road safety analysis, providing valuable insights for road safety management.

Improving Traffic Safety in Existing and New Road Tunnels with the Novel NDBA Concrete Safety Barrier

Abstract Two main elements are essential in terms of road traffic safety. The first element is accident prevention and the second is the minimization of accident severity once a crash has occurred. Concrete safety barriers have very good anti-collision performance against roadside obstacles, relatively modest construction and maintenance costs, and low dynamic deflection and therefore are widely used in tunnels. Thanks to their characteristic redirective profile these barriers can redirect errant vehicles into their original lane after collisions. However insufficient research has been done for increasing the performance of concrete barriers purposely designed for tunnel installations. This research presents the new “NDBA Tunnel” concrete safety barrier designed and constructed by the Italian Road Operator ANAS indicated to be installed in road tunnel sections for safety improvements. In Europe, road safety barriers must be designed in compliance with the European Standard EN 1317. Therefore, the barrier “NDBA Tunnel” was subject to the TB11 and TB81 full-scale crash tests according to the European EN 1317 regulation. The results prove the barrier's ability to absorb impact loads of light and heavy vehicles with a working width W2. Therefore, the NDBA concrete barrier can be installed on existing or new tunnels at a distance less than or equal to 70 cm from the facing of the tunnel wall.

Inclusive assessment of road traffic accident associated with design-construction disparities and contemplating its relative impact for sustainable road safety

Purpose Road accident is a major threat to sustainable road safety, causing immense suffering and posing an increasingly serious global challenge, especially in developing countries. It is the leading cause of death, injuries and property damage. While vehicle driver-related factors play a significant role in accidents, poorly designed and constructed roads are also a growing factor. As result, this study aims to assess traffic accident problems associated with design-construction complications on Arba Minch-Jinka Road, Ethiopia. Design/methodology/approach From 2013 to 2021, a large amount of traffic accident data was gathered, and through actual roadway surveys at potential locations along the road, the data was associated with design-construction parameters. The analysis was done by adopting descriptive statistics incorporating comparative hypotheses, in which the individual and combined effects of design-construction issues were identified. Results revealed, on average, 76% of total coincided accidents along the study road were associated with design-construction issues. Exclusively, causing factors, i.e. roadway, driver, vehicle, pedestrian problems and environmental, contributed 7.65%, 77.78%, 6.17%, 6.05% and 2.35% traffic accidents, respectively. Findings Detailed and time-consuming data collection, investigations, analysis and assessments were used in the research to discover a strong association between road design-construction problems and traffic accidents. As a result, 42 black spot sections were identified, and 7.65% is exclusively caused from design-construction problems. Curved road sections led the surge by 42% from selected design-construction variable, whereas the remaining 58% was shared among four parameters. According to relative analysis, design-construction issues caused a 58.17%, 12.14%, 32.36% and 29.93% increase in accidents in combination with driver, vehicle, pedestrian and environmental factors, respectively. This is in an average of 33.15% escalated problem in a combination that raises questions about the sustainability of road safety. Originality/value It is essential to use scientific methodologies to evaluate traffic accidents and associated design-build discrepancies in developing nations like Ethiopia if we are to achieve sustainable road safety. The fundamental importance and value of this study is that it promotes accountability to the road design and construction, which are not frequently thought of as influencing factors in traffic accidents. This paper is original, and all references have been correctly mentioned, to the best of the author’s knowledge.

A low-carbon route optimization method for cold chain logistics considering traffic status in China

In the paper of cold chain logistics, it is necessary to consider both traffic status and carbon reduction simultaneously. In this paper, an improved BPR (Bureau of Public Roads) road impedance function is designed, which reflects the traffic status in China under congested status more accurately. A low-carbon cold chain logistics route optimization model considering the traffic status in China is constructed, considering the multiple impacts of traffic status on total delivery cost, freshness of fresh products, and carbon emissions. To address the challenges posed by this multidimensional and discrete model, an improved discrete firefly algorithm (IDFA) is proposed. The numerical result demonstrates that IDFA has higher solving efficiency and better quality of the obtained solutions. Moreover, this paper also analyzes the impact of traffic status, vehicle types, and carbon trading prices on cold chain logistics delivery, as well as the comprehensive impact of traffic status and carbon trading prices. The proposed model is suitable for cold chain logistics enterprises with a single delivery center, active emission reduction willingness, and mostly delivering in congested road sections with high traffic volume. It offers valuable guidance for decision making and management in low-carbon cold chain logistics delivery.

Open-source data alternatives for regenerating urban road fine-grained features

The extraction of urban road features provides indispensable support to numerous high-accurate applications such as autonomous driving and urban high-definition mapping. However, approaches mainly focus on road connectivity, while often overlooking finer details of urban road constituent structures. Data that captures road details, such as LiDAR, may not be always readily available. This article proposes an operational framework for mapping fine-grained urban road features by integrating open-source data (OSD). The geometric measurement method is successively presented using projective geometry and prior knowledge for urban road sections. And a feature generation strategy is introduced to achieve and express the fine-grained road features. Compared with the corresponding large-scale topographic map (LTM) and available optical remote sensing image (AORSI), the proposed method regenerated fine-grained features of urban roads with m-level. It provides a cost-effective innovative and alternative method to acquiring fine-grained road datasets in other data-scarce regions.

Evaluasi Kinerja Konsultan terhadap Manajemen pada Pekerjaan Ruas Jalan Lambaro - Pidie

The development project on the Lambaroe-Pidie national road is expected to be carried out according to plan. This can be realized with the role of a team of Project Management Consultants within the Aceh National Road Implementation Center who carry out construction management including implementation and control in program preparation, technical planning, construction implementation and supervision, quality control, service and supply of materials and equipment. The purpose of this research is to evaluate the factors that determine the effective performance of consultants and evaluate the performance indicators of consultants on management on the Lambaroe-Pidie national road section. The research method is a mixed method, which is a method that combines qualitative and quantitative methods. The sampling technique used is quotas. This research was conducted by distributing questionnaires to the owner, project officer, PT. Citra Diecona, Contractors and Technical Assistance Team (Bantek) with a total of 13 respondents. Questionnaire tests include validity tests and reliability tests. Based on the results of the study, the validity test obtained a value of Rcount > Rtable with a value of 0.552, this indicates that the question item is valid. In the reliability test, a value of 0.694 was obtained, this indicated that the respondents' answers were reliable. Based on the results of the descriptive analysis the initiative variable (X5) has the highest value of 4.692, this explains that the respondents are very satisfied with the consultant's performance on the initiative aspect. The ability to communicate (X2) has the lowest value with a mean value of 4.369. although this variable has the lowest mean, the results of the study show that respondents are satisfied with the consultant's performance on the communication aspect. The evaluation of the consultant's performance on management on the Lambaro - Pidie road section has met the road performance indicators in accordance with the 2017 Public Works Regulations concerning road performance indicators on management on the Lambaro - Pidie National Road section.

Structural Health Monitoring of Bridges with Personal Laser Scanning: Segment-based Analysis of systematic Point Cloud Deformations

Abstract. Bridge structures can be surveyed using a number of different methods. Established are image-based methods using structure from motion by an unmanned aerial vehicle (UAV), terrestrial laser scanning (TLS), or a combination of both methods. Beyond static terrestrial laser scanning, buildings can also be efficiently surveyed using personal laser scanner (PLS) systems. The advantage here is the greater flexibility and increased speed compared to the static method. On the other hand, the accuracy may be more critical, and the resulting point cloud will be more sensitive to systematic global or local deformations under unfavorable measurement conditions. For example, temporary influences can lead to local mapping errors. These include influences such as uneven measurement system motion or non-static, feature-sparse environments. This study investigates the acquisition of 3D point clouds representing the outer shell of a concrete bridge using a PLS system. We demonstrate a method for detecting possible deformations in PLS point clouds using the example of a bridge structure. For this purpose, the reference (TLS) and the PLS point clouds are segmented into individual clusters and a segment-based ICP fine registration is performed. Different RMSE values for the upper road section (0.061 m) and for the pillar segments (0.021 m) as well as different transformation parameters indicate slight displacements in the PLS point cloud. The analysis of the cloud-to-cloud distances showed that there were slight deformations in the Z direction in the area of the road surface. In the lateral direction, no significant residual deviations were found in the area of the bridge pillars.

Safety Impact Prediction of Redesigning National Roads Crossing Residential Areas: An Italian Case Study

The purpose of this study is to determine the safety effectiveness of an intervention on an existing road by using predictive methods. Predictive methods allow the benefit of the intervention to be quantified in terms of crash reduction. Currently, the most widely used model is reported in the Highway Safety Manual, developed in the US. The HSM model is adapted to the Italian context through a calibration procedure. The model is then applied to two future scenarios: in the absence and presence of intervention. The redesign intervention consists of rehabilitating some road sections and constructing five tunnel bypasses to avoid crossing residential areas. The comparison between the ‘with’ and ‘without’ scenario estimated an overall reduction in the number of accidents of around 45%. The variant scenario is based on reasonable assumptions that allowed the determination of the proportion of traffic that will be diverted to the variant. In addition, several alternative future scenarios are considered to assess a possible different trend in assumed traffic distribution. Moreover, a possible overall increase or reduction in total traffic affecting the road is taken into account. The results showed that the intervention provided significant benefits even with increased traffic, proving the resilience of the intervention.

Survey of driver's functional state change, considering movement through mountain passes

According to traffic accident statistics, the main causes are violations of traffic rules. Based on scientific research, it is clear that the main reason for these events is the drivers' incorrect assessment of the road situation and their inadequate response. Assessing road conditions depends on drivers' qualifications, skills, work experience, reaction time, and other physiological factors. The functional state of drivers is important to consider. It reflects their ability to work reliably and affects both fatigue levels and how fatigue builds up. Factors that impact decision-making speed and quality are crucial when evaluating the risks of the transportation process, particularly those associated with human behavior. This study investigates the safety of freight transportation for drivers, road users, third parties, and the environment. The study focuses on road traffic characteristics in mountainous conditions at high altitudes. The study aims to analyze how drivers' performance is affected while navigating challenging sections of mountain roads in the Ukrainian Carpathians. Four different routes will be examined. The research will provide graphic analysis of the results. It will show the main patterns of changes in drivers' functional state based on the route's complexity. The research aims to analyze indicators of drivers' functional state and their impact on their performance reliability. It allows for a more detailed evaluation of transport routes and planning of truck drivers' work and rest schedules on suburban routes.

Machine Learning-Driven Calibration of Traffic Models Based on a Real-Time Video Analysis

Accurate traffic simulation models play a crucial role in developing intelligent transport systems that offer timely traffic information to users and efficient traffic management. However, calibrating these models to represent real-world traffic conditions accurately poses a significant challenge due to the dynamic nature of traffic flow and the limitations of traditional calibration methods. This article introduces a machine learning-based approach to calibrate macroscopic traffic simulation models using real-time traffic video stream data. The proposed method for creating and calibrating a traffic simulation model has significantly improved the statistical correspondence between the generated vehicle characteristics and real data about cars on the simulated road section. The correspondence has increased from 37% to 73%. Machine learning models trained on generated data and tested on real data show improved accuracy rates. Mean absolute error, mean square error, and mean absolute percentage error decreased by more than two orders of magnitude. The coefficient of determination has also increased, approaching 1. This method eliminates the need to deploy wireless sensor networks, which can reduce the cost of implementing intelligent transport systems.

Urban Roadside Flooding Analysis Using SWMM: A Case Study of a Road Section in Pokhara Metropolitan City, Nepal

Pokhara City, in Nepal, experiences heavy rainfall during four months of monsoon, causing stress on drainage infrastructures. This situation is exacerbated by poor drainage systems, ineffective urban planning, and rapid urbanization. This study aims to develop mitigation strategies for urban roadside flooding in the Barahi Chowk region in Pokhara City. The focus is to identify the causes and potential solutions for the recurring issue of urban roadside flooding. For this purpose, the study utilizes Storm Water Management Model (SWMM) computer modeling to analyze the hydraulic capacity of existing drainage systems during peak flows. The SWMM modeling reveals that the current drainage usage is between 80% and 100% during peak times, leading to flooding. Consequently, resizing or expanding various drainage sections using SWMM modeling is suggested. The study introduces Low Impact Development (LID) controls, such as rain gardens and permeable pavements, to manage surface runoff. Implementing rain gardens on just 3% of the impervious area in each sub-catchment showed an average 21.5% reduction in peak runoff and an average 6.68% reduction in the total runoff while implementing 5% in each sub-catchment, permeable pavements reduced peak runoff by 22-26% and total runoff by 8-11%. The research explores the impact of land use and land cover change and unplanned urban growth on roadside flooding, resulting in impermeable urban surfaces that disturb the natural drainage system and infiltration pattern. Thus, the outcomes of this study should be carefully considered by policymakers and stakeholders to address issues through sustainable urban planning and infrastructure development. Also, implementing measures like resizing drains and LID controls appears to be effective in controlling flooding during the study period and should be considered for future studies as well.

Influence of Base Layer Thickness and Property on Flexible Pavement Behavior

When designing the pavement layers, a suitable thickness must be chosen to protect the pavement from environmental conditions and traffic loads and ensure the structure's durability up to the design life. To investigate the behavior of flexible pavement, the characteristics and thickness of each layer are programmed into the finite element method (FEM). The Abaqus program is one of the infinite-element analysis programs. The use of the Abaqus program leads to a reduction in cost and time compared to laboratory tests. In this study, the Abaqus program analyzed a three-dimensional model of a multi-layered road section, and all materials have elastic behavior. The model comprises five layers (wearing, binder, base, subbase, and subgrade). The model was looked at with different base layer thicknesses (15, 25, and 30 cm) and elasticity moduli (1655, 2070, and 3000 MPa). Critical parameters were looked at in the present research: vertical displacement at the wearing layer's top, horizontal tensile strain in the asphalt layer's lowest point, and vertical compressive strain at the subgrade's surface. The outcomes indicated that the pavement is more susceptible to rutting than fatigue as a result of static load. An increase in thickness and modulus of elasticity for the base layer leads to a reduction in rutting risks.