Axle Configurations Research Articles

Study of the Influence of the Variability of Traffic-Related Parameters on the Service Life of Flexible Pavement Structures in Senegal by a Mechanistic-Empirical Approach

The results of the study showed that exceeding the axle load and axle configuration are indisputably among the most damaging factors for flexible pavement structures in Senegal, made of local materials (Diack basalt, Sindia laterite). The regulatory axle load recommended by UEMOA for users is set at 11.5 tons and 12 tons for a single and twin axle respectively. For calculation purposes, this load is set at 13 tons. However, in Senegal, this axle load is often exceeded, and given the diversity of heavy goods vehicles in traffic, single axles, whose effects, according to several authors, are more detrimental to flexible pavement structures, are increasingly observed in road traffic. Differences in fatigue cracking and rutting damage between single and dual wheels, as well as load overruns, show the need to take axle configuration and possible overloads into account when dimensioning flexible pavement structures in Senegal, and when planning their maintenance, the costs of which are excessively high, according to Senegal's Autonomous Road Maintenance Fund (FERA). Keywords: Single wheel, dual wheel, damage, fatigue cracking, rutting, traffic

Using the load distribution between girders to monitor the condition of bridges

This study looks at the load distribution among beams in a 3-dimensional bridge Finite Element Model under normal traffic loading and the resulting effect of damage, modelled as a localised loss of elements in a beam. The load distribution is captured, both transversely across the girders and also longitudinally along the girders, and used to identify damage that is remote from the strain sensor location. When there is a loss of elements in a section of the bridge (e.g. due to a strike from a vehicle passing underneath), a portion of the load will redistribute along alternative load paths in the structure. This is most pronounced when the position of the loading and the location of the damage align but also happens when they do not. The study examines the effect of vehicles of different weight and axle configuration on the load distribution, and how grouping results by axle configuration can overcome this. A further novelty of this approach is that the strain response can be transformed into an influence line, which then allows data from large populations of general traffic to be used irrespective of axle configuration. The effect of various transverse positions of vehicles within the driving lane is overcome by combining data from large populations of vehicles. An advantage of this method is that the load distribution from a vehicle crossing is calculated as a ratio i.e. when the bridge is experiencing the same general environmental conditions, and thus reducing the difficulty in controlling the effects of varying environmental conditions when comparing results to a healthy baseline.

Frequency Identification using Resonance Curve-Based Drive-by Monitoring: Field Validation

Railway bridges have a long service life - in Germany, for example, the average is 122 years. During this time, vehicles are constantly evolving, leading to innovative axle configurations and higher speeds. This leads to loads for which the bridges were not originally designed, which can lead to resonant structural responses. A key parameter for calculating and evaluating the dynamic behaviour of bridge structures, is the resonance frequency. Due to the large number of bridges in the network, conventional methods using sensors on the structure would be very laborious. A cost-effective alternative would be drive-by monitoring, using sensors on a passing train. In railway bridge contexts, drive-by monitoring to identify frequencies faces challenges from short spans and high speeds, leading to brief contact periods. The brief periods cause a low resolution of the signals in the frequency domain. An approach to overcome this issue is the use of resonance curve-based drive-by monitoring. The term resonance curve describes the maximum structural responses as a function of speed. In conjunction with the known axle configuration of the train, the resonance frequency can be determined from the resonance curve. In this paper, data from two field tests are analysed, in which synchronised acceleration measurements were conducted on the main girders of the bridges and the axle boxes of the trains. An ICE 4 was used on a bridge with a 19.5-metre span, and an ICE TD on a bridge spanning 16.4 metres. The analyses show that frequency identification using indirect resonance curves is feasible under real operating conditions. Thus, this approach enables the determination of a key parameter essential for calibrating structural models. Furthermore, this method enables the avoidance of resonance crossings by speed adaptation, either by acceleration or deceleration. This strategy has the potential to significantly increase the service life of bridges.

Evaluation of equivalent axle load factors for multi axles based on fatigue tests using actual strain waveforms

Equivalent axle load factor (EALF) is used to characterize the fatigue damage effect of multi-axle loads on asphalt pavement. EALF is calculated as the ratio of the pavement’s fatigue resistance under a single axle load to that under a multi-axle load. Existing studies use the same fatigue life function to predict the fatigue life of asphalt mixture under both single- and multi-axle loads, primarily focusing on the differences in pavement strains under these two configurations. However, strain waveforms in asphalt pavement caused by multi-axle loads differ from those under single-axle loads, altering the mixture’s fatigue behavior. To address this issue, this research tests the fatigue responses of asphalt mixtures under actual loading waveforms from single-axle, tandem-axle, and tridem-axle loads. Based on the test results, fatigue life functions are developed for each axle configuration and used to establish an updated EALF model. Since the applied fatigue life functions are based on test results from more realistic strain waveforms, the calculated EALFs provide more reliable predictions of the damaging effect of multi-axle loads on asphalt mixtures.

Finite Element Modeling to Predicting Rutting in Flexible Pavements under Overloading

Road infrastructure is seriously threatened by heavy vehicle overloading, causing substantial damage, particularly rutting. This study uses advanced finite element analysis (FEA) techniques to improve pavement performance prediction. Six models were created using the ABAQUS/CAE program to evaluate the rutting performance of flexible pavement under overloaded conditions. These models simulated the existing pavement design and a proposed design, each subjected to three axle load configurations: single axle-single tire, tandem axle-dual tire, and tridem axle-dual tire. The research includes conducting surveys on traffic volume and axle load, to precisely evaluate the current traffic situation and identify problems associated with overloading. Core extractions enabled a thorough comparison of the existing pavement's thickness, density, and material characteristics with the proposed design. Based on these findings, a new design for a flexible pavement was developed, focusing on enhancing its ability to withstand rutting. The analysis determines that the existing pavement cannot withstand overloading vehicles, necessitating a 6.67% increase in the thickness of the surface, a 37.5% increase in the thickness of the binder, a 50% increase in the thickness of the base, and a 32% increase in the thickness of the subbase layers. Significantly, these modifications and improvements to material qualities were discovered to effectively decrease rut depth, an important factor in the durability and performance of pavement.

Analysis and Design of Flexible Pavement and Cost Comparison with Cement-Treated Base and Subbase Material

Road transport is important in economic, social; and a country’s overall development. Various commercial vehicle classes have utilized roads with different axle configurations and loads. Due to the cumulative effect of wheel loads and the aging of bitumen binder flexible pavement starts deteriorating. The bitumen pavement failure is mainly due to fatigue cracking as well as rutting deformation. Thus, proper load analysis for the intended period of pavement planned life needs to be analyzed and the pavement designed accordingly. The development of software such as IITPAVE enables the calculation of stress and strain values at required points across various pavement layers. The project's goal is to gather traffic data as well as soil CBR values from the field to design a flexible pavement following IRC: 37-2018 guidelines. The pavement would be analyzed using IITPAVE Software to obtain the actual strains at required critical points. Pavement design is influenced by factors such as properties of subgrade soil, wheel load, climatic conditions, and pavement materials. Pavements are built according to IRC guidelines and MORTH specifications. Excessive strain along with the deformation at the critical locations in pavement are the primary causes of bitumen pavement failure. This research aims to design a flexible pavement and compare the cost of traditional pavement layer composition with cement-treated base as well as sub-base materials. Keywords: Flexible Pavement, Cement treated base (CTB) and Subbase (CTSB), Cost Comparison.

A case study on scenario-based optimization for axle load survey data selection for flexible pavement design in Vietnam

The unique traffic patterns in Vietnam, characterized by a mix of vehicle types, axle configurations, and overloading, pose challenges to current flexible pavement design methods. This study investigates how selecting different vehicle axle load survey data scenarios impacts the accuracy of pavement design and rehabilitation for roads in Vietnam. Evaluation of various data selection methods and their influence on pavement response using the current flexible pavement calculation procedure in Vietnam. By comparing the pavement design criteria calculated under each scenario, this research aims to provide clear guidelines for engineers choosing appropriate axle load data for pavement design. This, in turn, will lead to the design and maintenance of more durable and sustainable pavements, ultimately promoting a more efficient and resilient transportation infrastructure in Vietnam. The research approach involves analyzing various axle load survey data scenarios, including those representing typical traffic conditions, overloaded vehicles, and specific vehicle types. The calculated pavement responses under each scenario are then compared to assess the impact of data selection on design outcomes. This study's findings are expected to provide valuable insights for pavement engineers in Vietnam, enabling them to select appropriate axle load data for accurate pavement design and rehabilitation. This will contribute to building more durable and sustainable road infrastructure, resulting in a more efficient and resilient transportation network

Studying the Impact of Soil Stabilization Techniques on Rigid Pavement Joints Across Various Axle Loads

Rigid pavement slabs are erected on a prepared subgrade or foundation layer, providing a hard and continuous surface. Transverse joints made of dowel bars connect them, and longitudinal joints made of tie bars join them longitudinally. This study is an investigation of the impact of soil strength and concrete parameters on the effectiveness of dowel bars in rigid pavements. Moreover, three parameters were examined; California Bearing Ratio (CBR), concrete compressive strength and slab thickness. The analysis was conducted using the Ever FE program and focused on several axle configurations applied to the joint. The results indicate inverse association between the pavement slab thickness and the concrete strength, under the assumption of consistent soil strength. Moreover, an assortment of reduced shear forces on the dowel bars is seen when the soil strength values increase. It indicates that soil strength has a greater impact on the shear load of dowel bars compared to the qualities of concrete. Additionally, the type of axles used and the magnitude of soil strength were shown to have a significant effect on the shear load.

Deep learning-based identification of vehicular moving forces for bridges without axle configurations

This study proposes a novel moving force neural identifier (MFNI), a deep neural network designed for accurately estimating dynamic vehicular axle loads without knowing the vehicle speed and axle configurations (i.e., axle number and spacing). The MFNI architecture comprises a multi-time resolution encoder/decoder (MRED) and a dynamic moving force correction block (DMF-corr block). Firstly, the MRED with hierarchical resolution is developed to adapt to the complex dynamic inverse problem-solving. It can capture the multi-time resolution features of bridge responses and dynamic moving forces, and perform stably under various lengths of identification sampling windows. Then, the DMF-corr block limits the range of identified values by assuming that the vehicular excitation on the bridge is unidirectional, which enables the MFNI model to better determine the axle number, vehicle speed, as well as whether the axle is acting on the bridge. Numerical studies are implemented to confirm the accuracy and efficiency of the proposed MFNI approach, and a parametric sensitivity analysis is conducted to evaluate the robustness of the approach. Finally, a laboratory experiment confirms the practicability of the MFNI in detecting vehicular moving forces with a limited number of sensors and training samples. Both numerical and experimental results demonstrate the potential of the proposed method to serve as a nothing-on-road bridge weigh-in-motion system in practical engineering.

The Effect of Axle Overloading and High Tire Pressure on Flexible Pavement Structure

Axle overloading and high tire pressures on the highways and motorways in Pakistan are one of the reasons that cause early pavement deterioration. There are numerous sections on the national highway on which trucks are reposted to be operating at 40-80 percent higher tire pressure than the legal limit, and the axle overloading is 30 percent greater than the legal axle load limit. This research aims at determining the effect of axle overloading and high tire pressure on the flexible pavement structure and derive the truck factors for trucks in order to quantify the damage to the pavement due to a single pass of 2-axle, 3-axle, 4-axle, 5-axle, and 6-axle truck using the results reported in the Pilot Axle Load Survey conducted by the National Transport Research Centre. In order to determine the effect of axle overloading and high tire pressure, a theoretical linear elastic mechanistic empirical analysis for different axle configurations was performed using KENLAYER and regression models were developed to find the Equivalent Axle Load Factor (EALFs) for the fatigue cracking, and permanent deformation. It was found that the EALFs were mostly controlled by permanent deformation distress criterion. The EALFs and the truck factors were highly influenced by the axle loads rather than the tire pressure. The 3-axle truck was found to be the most damaging truck followed by 6-axle truck, 5-axle truck, 2- axle truck, and 4-axle truck.

Dynamic rollover-safety index-based tilt optimisation encompassing road configurations for narrow three-wheelers: Balancing energy efficiency and ride comfort

The active tilt-controlled narrow three-wheelers (3Ws) equipped with a closed cabin aim to offer a comfortable driving experience comparable to four-wheelers while maintaining the manoeuvrability of two-wheelers without compromising on speed. Based on this concept, this study explores a tilt control strategy for narrow 3Ws. While previous research has established a steady-state tilt angle considering a zero-track width, this study incorporates track width due to the multi-wheel axle configuration. This novel approach not only withstands unbalanced lateral acceleration but also saves significant tilting torque. Unnecessary tilting is minimised by introducing a tilt actuation system (TAS) based on a unique dynamic rollover index. Central to the original contribution is the stability margin (SM), a dynamic rollover-safety index considering longitudinal and lateral dynamics, surpassing the traditional rollover index load transfer ratio, particularly for delta 3Ws. This work proposes a desired SM threshold-dependent steady-state tilt angle, activating TAS only when necessary. This pioneering method optimises the desired SM threshold using goal programming. Additionally, this research addresses a critical oversight in previous studies by accounting for the influence of road slopes, ensuring consistent stability across diverse road conditions. It is crucial to note that the proposed rollover index-based tilting approach markedly outperforms the conventional methods, reinforcing its originality and potential for future vehicular design.

Fatigue damage caused by superload vehicles in concrete pavements

Superload vehicles (SLs) are typically defined as vehicles having a gross vehicle weight (GVW) greater than 890 kN. SLs often consist of unique axle configurations that may cause significant damage to pavements. Research has been mainly limited to SLs on asphalt pavements, therefore the effect of SLs on concrete pavements is not well established. In this study, fatigue stresses in concrete pavements were quantified for a database of pavement structures and SLs to identify critical conditions that contribute to fatigue damage. A series of load pulses were constructed from a database of finite element results to identify conditions and locations within the slab for peak stress development. Tensile stress greatest in thin pavements with a stiff base layer and large positive temperature gradients subjected to tandem axle SLs. Fatigue damage was calculated for the critical cases using several damage models, and significant variation was found between models based on inputs used.

Impact of Heavy Vehicle Axle Overload and Axle Configuration on Road Damage in Afghanistan

Aim: This study aimed to determine the percentage of heavy vehicles, overloaded vehicles, and heaviest vehicle that leads to deterioration of asphalt roads. Furthermore, the study aimed to assess the impact of ESALs and axle configuration on asphalt thickness and subgrade.
 Methods: This research used quantitative truck traffic data collected for three months in the Laghman WIM (Weigh in Motion) station located on the Kabul Torkham National Highway. Observed axle loads and GVW (Gross Vehicle Weight) data collected from April/ 10/2022, up to June/7/2022 average daily truck traffic of 73895 was estimated axle loads converted to the standard axle ESALs (Equivalent Single Axle Loads).
 Results: The percentage of heavy overweight vehicles is 13% while the heaviest vehicle is T2-Bedford truck vehicles at 20.17%. The T2 Bedford truck percentage was 42.17% in overall volume; this truck was overloaded 20.17%, compared to the general trend of Ministry of Public Works (MoPW), the T3 Hino truck contribution was 1.24% in total volume and 18.64% was overloaded, the ST112 semi-trailer contributed 3.02% in total volume, and 8.52% were overloaded. The ST113 5-axle and TT123 6-axle trailers percentile in entire volume was 9.6 % and 40.85% whereas, the overloading degree for these heavy vehicles was 2.29% and 6.72% respectively.
 Conclusion: Overloading percentage is 13% while, T2 Truck is the heaviest vehicle The variation of ESALs and axle configuration on asphalt thickness and subgrade modulus illustrates the higher thickness of asphalt decreases the damage to asphalt roads.
 Recommendations: Afghanistan Weigh-in-Motion stations need professional employees, internet facilities, electricity, and proper databases to record the data. By applying tight legislation and fines overloading will be minimized. Researchers may also research heavy vehicle tires' impact on road damage. Furthermore, it needs to determine the level of fatigue cracking and rutting failures by overloading.

Generation of traffic input for flexible pavement design

Layered elastic theory (LET) was performed by Burmister. It helped to build mechanistic – empirical (M-E) pavement design. In this study, three different approaches were used to predict Cumulative Equivalent single axle load (C-ESAL) over the design period. Two were based on M-E and one was empirical. In each of these cases, standard axle loads were used as well as weight limits and vehicle classification, according to their axle configurations (single, tandem, tridem). Traffic data came from annual traffic census campaigns over the past ten years. Gross vehicle weight (GVW) and axle weight (AW) data came from a fixed weighing station performed during 31 days in 2020. Two road axis were considered: One having a weighing station (reference road) and one under technical studies (specific road). Traffic road data were used to perform regression analyses and predictions. AW and GVW helped to calculate Axle load equivalency factors (ALEF) and Truck equivalency factors (TEF) on the reference road. These values were projected on the specific road. Frequency distribution, gross vehicle weight distribution, axle load distribution of heavy vehicles are applied on the reference road. We performed overload AW and overload GVW analyses. Comparisons were done for the three approaches and an evaluation of technical studies was proposed, including traffic and AW monitoring and management systems. This work came as a basis for the transposition of M-E calculation of traffic inputs, more accurate and used over the passed fifty years, in Higher Income countries, called AASHTO method for USA, LCPC-SETRA method for France, to Cameroon and Sub-sahara African countries, that have been using empirical generation of traffic inputs over the same period, called CEBTP method.

LiDAR Vehicle Point Cloud Reconstruction Framework for Axle-Based Classification

As Light Detection and Range (LiDAR) technology rapidly advances, it is becoming increasingly viable as a solution to collect vehicle classification data. The main challenge of LiDAR compared with video in vehicle classification lies in its resolution, which limits the ability of LiDAR-based models to classify vehicles in detail from a single captured frame. This paper proposes a novel framework for reconstructing the vehicle point clouds generated by a roadside LiDAR sensor, by considering ground plane constraints and developing a bootstrap aggregating deep neural network (bagging DNN) model to classify the reconstructed vehicle point clouds, according to the US Federal Highway Administration (FHWA) axle-based vehicle classification scheme. First, a probabilistic-based registration algorithm is used to estimate the transformation matrix between consecutive frames of each vehicle point cloud. Then, a multiway registration is conducted to fine-tune the estimated transformation matrices to rebuild the 3D model of each moving vehicle. Second, key features are extracted from the reconstructed vehicle models and fed into a bagging DNN model to provide classifications based on the FHWA scheme. The classification model with the reconstruction framework outperforms the latest developed LiDAR-based FHWA classification model in terms of both accuracy and robustness. The model has an 83 percent average correct classification rate (CCR) on the test set. Remarkably, the proposed model can accurately distinguish Classes 5 and 8 trucks, which have overlapping axle configurations, with a 97 percent and a 90 percent CCR, respectively.

Incorporation of Pavement Dynamic Loading in Mechanistic–Empirical Design Frameworks

A framework for incorporating dynamic loading in pavement design is introduced. The framework is composed of five main steps. Firstly, input parameters, such as traffic characteristics, material properties, and the pavement configuration, are determined. Both primary and secondary data were obtained from the literature in this step. Secondly, a database of critical pavement responses, used by AASHTOWare software’s transfer functions to calculate pavement damage, was built using advanced pavement finite element models after the loading input was defined. The database includes various pavement configurations, axle configurations (single and tandem), pavement material properties, temperatures, loading conditions, and tire types (single steering, dual, and wide-base). AASHTOWare’s transfer function predicts pavement damage from pavement responses and is used to calculate the international roughness index (IRI) in the third and fourth steps, respectively. Finally, the load spectrum is adjusted to incorporate roughness-induced dynamic loading once the IRI exceeds 95 in./mi. A simple analytical dynamic-loading model was developed, based on mechanistic truck–trailer results. The model is a function of the tire configuration, speed, and IRI. Multiple case studies were performed, considering various pavement configurations, material properties, average annual daily traffic values, and dynamic-loading percentiles. Results showed that dynamic loading had the most significant impact on fatigue life, followed by rutting potential. The AASHTOWare’s transfer functions were found to be insensitive to an increase in loading when considering thick-pavement structures. The outcome of this effort was validated using the measured and predicted IRI from the Specific Pavement Study sections, which are part of the Long-Term Pavement Performance program.

SIMPLIFIED MECHANISTIC – EMPIRICAL ANALYSIS OF FLEXIBLE PAVEMENT

Pavement stress-strain analysis is an ideal tool for analytical modelling of pavement behaviour and thus, constitutes an integral part of pavement design and performance evaluation. It is the fundamental basis for the mechanistic design theory. Predicting pavement response by simplified procedure analysis by relying on equivalency factors using axle load spectrum which is obtained from Weigh-In-Motion (WIM) data is aimed for this study. The framework for computing the structural response of the standard axle group loads on a pavement structure by using a layered elastic computer program and calculation of pavement responses for axle load distribution for different axle groups and axle types by using the theoretical analysis. From the study, the summary of the obtained results are as follows: (1) axle load distribution was developed for the four considered axle configurations; (2) Single axle with single tyre has the greatest destructive impact followed by the tridem axle with dual tyres (TRDT) and next by TADT. The least destructive axle group type is the Single Axle with Dual tyre SADT.The predicted pavement response by theoretical analysis indicates that the critical tensile strains obtained results are all greater than the critical vertical strains. At the heaviest axle load, from 70KN, for both SAST and SADT; from 140KN for TADT; and from 210KN, the critical strains have the greatest magnitude by SAST and followed by SADT and next by TADT. The least critical tensile strain is from the TRDT.

Truck platoon analysis for autonomous trucks

Selection of optimum platoon pattern based on types of trucks inside the platoon, the number of trucks in the platoon, headway distance, interplatoon distance as well as the use of different lateral wander modes for autonomous trucks has been analyzed. The objective of this research is to study the impacts of axle configurations, truck grouping, headway distance and lateral wander options on the performance of truck platoons. Four different headway distances from 2 to 5 m are compared. The first platoon PT-1 only consists of semi trailers, the second platoon PT-2 only consists of rigid body trucks and the third platoon PT-3 consists of equally distributed random traffic mix. Analysis has been conducted using the dload subroutine for projecting zero wander and uniform wander movements for each truck in the platoon on a three layered pavement crossection at vehicle speeds of 90 km/h for a total of 15 years of pavement lifetime consisting of 1.4 million equivalent single axle loads in finite element software ABAQUS. Results show that PT-3 platoon yields the minimum accumulation of damaging strains when compared against other platoon types. A headway distance of 5 m is suggested when using a zero wander mode and 3 m when using a uniform wander mode. In case of zero wander mode, fatigue life of the pavement decreases by 1.2 years and the use of uniform wander mode delays the rutting by 1.6 years, thereby increasing lifetime of the pavement.

Comparative evaluation of dynamic responses of RCC composite pavement under different moving axles

Roller-compacted composite pavement is considered as an alternative for traditional pavements that provides the desired benefits of both rigid and flexible pavements in a cost-effective manner. To evaluate the performance of roller-compacted concrete (RCC) composite pavement under moving loads, a three-dimensional finite element model (FEM) was developed. A realistic dynamic moving load was applied to the surface of the pavement via DLOAD subroutines developed by FORTRAN. The dynamic response of the pavement at critical locations induced by single, tandem, and tridem axles at speeds of 8 and 80 km/h was determined using the developed FEM model and utilized to estimate pavement performance. Sensitivity analysis of design factors considering variations of hot mix asphalt (HMA) and RCC thicknesses, RCC elastic modulus, axle configurations, and moving speed was conducted to evaluate their impact on fatigue life and rutting development of RCC composite pavement. The results show that the performance of the pavement is significantly affected by axle configurations and moving speed. Among different axle configurations, the tandem axle creates the highest tensile stress and shear stress in the RCC base and HMA layer, respectively. The fatigue life of the pavement prolongs by increasing in the speed of moving loads, so it is expected that the pavement withstands higher load repetition when it is subjected to higher speed traffic. Moreover, increasing layer thicknesses and stiffness of the RCC layer improve fatigue life and rutting performance of the pavement. Even though increasing the thickness of the HMA layer enhances the fatigue life of pavement, increasing it to over 15 cm increases the potential of rutting.

A Study on the Design Depth of Permeable Road Pavement through Dynamic Load Experiment.

This study investigated vertical strain and stress through a dynamic load experiment at the testing area of Ke-Da Road, Pingtung, Taiwan. A thirty-five-ton truck was moved at constant speeds of 40, 60, and 80 km/h to simulate heavy load conditions to study the mechanical variations. From the results, it was found that the strain and stress curves of the permeable road pavement showed asymmetry due to the viscoelastic property of the open-grade friction course. The results showed that vertical strains and vertical stresses of permeable road pavement were greatly affected by the axle configuration and the change in traffic speed. Furthermore, to propose the design thickness of a permeable road pavement, the pavement strain and stress were modelled with respect to depth using regression based on these collected data. According to the stress regression models and considering the construction uncertainty, the recommend design depth of a permeable pavement is 30 cm. The findings of this study would be helpful in determining the permeable road pavement depth when subjected to heavy traffic load, and the material combination of open-graded friction concrete, porous asphalt concrete, and permeable cement concrete was proposed in this study during the design period.