High Traffic Levels Research Articles

Statistical Modelling of Traffic Noise Using Smart PLS-SEM In Urban Roads

The objectives of this study are to assess the traffic noise levels in Shah Alam, Selangor, Malaysia, and to propose traffic noise model among influential factors. Five factors and 20 attributes were measured at three locations using a sound level meter and analyzed using the PLS-SEM approach. The results of this study showed that high traffic noise levels on urban roads exceeded the maximum permissible limit of 60 dBA during the day, according to Malaysian guidelines. However, the integrated traffic noise prediction model approach has specific indirect effects: built environment -> climate conditions -> traffic flow.

Estimation of population exposed to road traffic noise in Kosovo highway using GIS modelling and roadside measurements

New highways have been introduced into Kosovo landscape in recent years. The trajectory of the highways crosses through the fields and in the middle of some previously remote rural settlements. This has changed the environment for these areas and the environmental noise is a major concern. This study aims to estimate the population exposed to high traffic noise levels around the highway routes in Kosovo. GIS has been used to model the highway lines, the terrain and the buildings on site. Roadside traffic noise measurements as well as traffic flow measurements have been conducted to approximate the noise sources. An approximate noise map has been generated for the studied area. The population exposed to daytime and nighttime road traffic noise were estimated. The results show the need for road traffic noise reduction measures and areas where they are most needed.

Sound insulation of partially open windows - alternative laboratory measurement methods

Sound insulation with partially open windows has had growing attention in recent years. In Denmark, this is primarily caused by the Danish Environmental Protection Agency's guideline from 2007 "Noise from roads", which introduces noise limits with open windows (opening area of 0.35 m2) for situations with a high traffic noise level. The sound insulation of traditional windows in open position have been measured in both the laboratory and external environment, and for certain setups too different results have been observed. To investigate the reasons behind the discrepancies, the traditionally reverberant source room of laboratory measurements was modified to a semi-anechoic room to remove reflections from unwanted reflections from room surfaces and to imitate the external environment during field measurements. Four different window types were tested as part of the research projects "Optimized measurement method for sound reduction of partially open windows part 1 and 2" (MetÅV and MetÅV2) in collaboration with four Danish window manufacturers. The primary focus of the project is to explore alternative laboratory methods to the traditional diffuse field method by studying reference cases from field measurements and taking into consideration different sound source positions and window geometry. This paper describes the results so far.

Enhancing Automated Vehicle License Plate Recognition with YOLOv8 and EasyOCR

This research focuses on the development of an automatic system for vehicle license plate recognition using YOLOv8, EasyOCR, and CNN methods for object classification. The main issue raised is the need for an accurate and efficient system for recognizing vehicle license plates in real-time in dynamic environments, especially in urban areas with high traffic levels. The method used in this study involves resizing the input image to 416x416 pixels to standardize the data, analyzing the YOLO architecture that divides the image into a 7x7 grid, and using the Convolutional Neural Network (CNN) algorithm for feature extraction and object classification. Object detection uses the YOLOv8 method which is tasked with recognizing license plates using a previously trained YOLO (pretrained model) model then implemented and tested using video with 4k quality to ensure its effectiveness in detecting vehicle license plate objects, followed by the Optical Character Recognition (OCR) process with the EasyOCR method to read text on license plates and tested to ensure its effectiveness in reading characters on license plates vehicle number. The purpose of this research is to develop a system that can improve accuracy and efficiency in vehicle license plate recognition. The results show that the accuracy, precision, recall and F1-Score for object detection reach 100% and the average percentage of detected text conformity is 74.66%, which shows that this system is reliable in real applications and contributes to the development of automatic license plate recognition technology.

Analysis of Decarbonization Potential in Mobility Sector with High Spatial Resolution: Study Case of the Metropolitan Area of Valencia (Spain)

This study addresses the urgent need for sustainable urban mobility through a comprehensive analysis of decarbonization potential in the metropolitan area of Valencia, Spain. The research is motivated by the imperative to mitigate climate change amidst high traffic and congestion levels. Utilizing the Origin–Destination matrix from the Valencian community’s mobility plan, the study prioritizes displacements for substitution by sustainable alternatives. Through a detailed case study analysis, critical areas for decarbonization are identified, and practical strategies to reduce carbon emissions are proposed. The methodology encompasses a thorough literature review on decarbonization measures, examination of existing plans, and analysis of sustainable trips with high spatial resolution using geographic information systems (GISs). The study identifies trips with significant decarbonization potential and assesses the current public transportation network. Spatial analyses illustrate demand patterns for sustainable transport options, emphasizing the need for tailored strategies. Key findings highlight the role of private and commercial transport in CO2 emissions, advocating for targeted interventions to enhance active transport infrastructure, promote carpooling, adopt low-emission vehicles, and improve public transport accessibility and efficiency.

Conflict management at urban bus stops through cooperative trajectory planning

Conflicts due to frequent bus dwelling and entering/exiting maneuvers at bus stops have significantly undermined the efficiency, safety, and sustainability of the urban bus system. This paper proposes a cooperative trajectory planning strategy in a Vehicle-to-Infrastructure (V2I) environment for conflict management between buses and cars at bus stops. A dynamic multi-stage-based model along with solution algorithm is developed to search trajectories that eliminate the conflicts between cars and buses entering and leaving the bus stop in real time.The assessment of the proposed strategy is carried out at both the bus stop and corridor levels within a simulated environment. In-depth trajectory analyses during a typical weaving process at a bus stop reveal that the proposed strategy effectively eliminates bottlenecks and enhances operational performance across multiple approach lanes affected by the bus stop. A thorough evaluation involving multiple cycles of weaving among buses and vehicles at the bus stop reaffirms the strategy’s effectiveness under varying levels of bus occupancies, traffic demand, and bus stop locations. The case study at the corridor level illustrates that the proposed strategy successfully improves operational performance and bus schedule adherence across diverse scenarios, encompassing different roadway link lengths, traffic demands, bus headways and dwelling times, and bus stop locations. It notably excels in enhancing the performance of an urban corridor with longer link distances and near-side located bus stops, particularly under high traffic demand levels and shorter bus dwelling times.

Assessment of genotoxicity of air pollution in urban areas using an integrated model of passive biomonitoring

Atmospheric pollution is a major public health issue and has become increasingly critical for human health. Urban atmospheric pollution is typically assessed through physicochemical indicators aligned with environmental legislation parameters, providing data on air quality levels. While the effects of pollution on sensitive organisms serve as a warning for public health decision-makers, there remains a need to explore the interpretation of environmental data on pollutants. The use of species adapted to urban environments as sentinels enables continuous and integrated monitoring of environmental pollution implications on biological systems. In this study, we investigated the use of the plant species Tradescantia pallida as a biomonitor to evaluate the genotoxic effects of atmospheric pollution under diverse vehicular traffic conditions. T. pallida was strategically planted at the leading urban intersections in Uberlândia, Brazil. During COVID-19 pandemic lockdowns, we compared indicators such as physical, biological, and traffic data at different intersections in residential and commercial zones. The reduction in vehicular traffic highlighted the sensitivity of plant species to changes in air and soil pollutants. T. pallida showed bioaccumulation of heavy metals Cd and Cr in monitored areas with higher traffic levels. Additionally, we established a multiple linear regression model to estimate genotoxicity using the micronucleus test, with chromium concentration in the soil (X1) and particulate matter (PM) in the atmosphere (X2) identified as the primary independent variables. Our findings provide a comprehensive portrait of the impact of vehicular traffic changes on PM and offer valuable insights for refining parameters and models of Environmental Health Surveillance.

Impact of environmental variables on COVID–19 – a study from the Telangana State, India

The objective of the present investigation is to compare the pollution levels during the lockdown and unlock period to the pre-lockdown phases of the COVID-19 pandemic and intends to investigate the relationship between COVID-19 incidences and atmospheric in Hyderabad, Telangana, India. Throughout the lockdown and unlock periods, pollutants in the atmosphere were significantly reduced; a significant reduction was observed in Hyderabad with higher traffic levels with a maximum reduction of PM2.5 and PM10 levels (60.3% and 53.4%, respectively) compared to pre-lockdown levels. The number of COVID-19 cases relative to most of the air pollutants was negatively correlated, which may be a mere coincidence as a result of the lockdown. The correlation test reveals a positive association between the ambient temperature and COVID-19 confirmed cases (r = 0.99, 0.07) during the lockdown phase and throughout the study period, suggests that the warm, tropical weather in the area of the study region is successful in preventing the spread of COVID-19. The findings of this study can help us comprehend how environmental variables play a part in the spread of COVID-19 in tropical and subtropical nations. The results of this study also suggest that temporary lockdowns useful tool for managing environmental imbalances.

Safe Hybrid-Action Reinforcement Learning-Based Decision and Control for Discretionary Lane Change

Autonomous lane-change, a key feature of advanced driver-assistance systems, can enhance traffic efficiency and reduce the incidence of accidents. However, safe driving of autonomous vehicles remains challenging in complex environments. How to perform safe and appropriate lane change is a popular topic of research in the field of autonomous driving. Currently, few papers consider the safety of reinforcement learning in discretionary lane-change scenarios. We introduce safe hybrid-action reinforcement learning into discretionary lane change for the first time and propose the Parameterized Soft Actor–Critic with PID Lagrangian (PASAC-PIDLag) algorithm. Furthermore, we conduct a comparative analysis with Parameterized Soft Actor–Critic (PASAC), which is an unsafe version of PASAC-PIDLag. Both algorithms are employed to train the lane-change strategy to output both discrete lane-change decisions and continuous longitudinal vehicle acceleration. Our simulation results indicate that at a traffic density of 15 vehicles per kilometer (15 veh/km), the PASAC-PIDLag algorithm exhibits superior safety with a collision rate of 0%, outperforming the PASAC algorithm, which has a collision rate of 1%. The generalization assessments reveal that at low traffic density levels, both the PASAC-PIDLag and PASAC algorithms are proficient in attaining zero collision rates. However, at high traffic density levels, although both algorithms result in collisions, PASAC-PIDLag has a much lower collision rate than PASAC.

Targeting fin whale conservation in the North-Western Mediterranean Sea: insights on movements and behaviour from biologging and habitat modelling.

Biologging and habitat modelling are key tools supporting the development of conservation measures and mitigating theeffects of anthropogenic pressures on marine species. Here, we analysed satellite telemetry data and foraging habitat preferences in relation to chlorophyll-a productivity fronts to understand the movements and behaviour of endangered Mediterranean fin whales (Balaenoptera physalus) during their spring-summer feeding aggregation in the North-Western Mediterranean Sea. Eleven individuals were equipped with Argos satellite transmitters across 3 years, with transmissions averaging 23.5 ± 11.3 days. Hidden Markov Models were used to identify foraging behaviour, revealing how individuals showed consistency in their use of seasonal core feeding grounds; this was supported by the distribution ofpotential foraging habitat. Importantly, tracked whales spent most of their time in areas with no explicit protected status within the study region. This highlights the need for enhanced time- and place-based conservation actions to mitigate the effects of anthropogenic impacts for this species, notably ship strike risk and noise disturbance in an area of exceptionally high maritime traffic levels. These findings strengthen the need to further assess critical habitats and Important Marine Mammal Areas that are crucial for focused conservation, management and mitigation efforts.

Evalusai Kinerja Simpang Tak Bersinyal (Study Kasus Simpang Jalan Sukomulyo dan Jalan Kyai H. Syafii Kec. Manyar Kab. Gresik)

The intersection of Jalan Sukomulyo and Jalan Kyai H. Syafii is one of the 3 unsignalized intersections with quite high traffic levels. So it is necessary to conduct research on the performance of the intersection. This type of research was conducted using field observation methods. The primary data collection is done by making direct observations at the Sukomulyo road intersection and Kyai H. Syafii road. The LHR survey was carried out for one week by directly recording vehicles passing through the planning location at 15-minute intervals. When the data have been obtained, it analyzed based on the Directorate General of Highways MKJI 1997. The results of the analysis of the performance of the intersection at the Sukomulyo road intersection and Kyai H. Syafii road show quite good results even though many vehicles pass it. Morning traffic volume is 4220.8 pcu/hour, afternoon is 2071.6 pcu/hour, in the afternoon is 3741.3 pcu/hour. The morning intersection capacity is 6552.74 pcu/hour, the afternoon is 4805.38 pcu/hour, in the afternoon is 5500.06 pcu/hour. The degree of saturation in the morning is 0.64, afternoon is 0.43 and afternoon is 0.68. Morning delay is 7.79 seconds/hour, afternoon is 3.98 seconds/hour, in the afternoon is 8.57 seconds/hour. Probability of queuing in the morning with an upper limit of 35.22% and lower limit of 16.98%, Probability of queuing in the afternoon with an upper limit of 20.44% and a lower limit of 8.5%, Probability of queuing in the afternoon with an upper limit of 38.78% and a lower limit of 18.98% .

High‐resolution model reconstruction and bridge damage detection based on data fusion of unmanned aerial vehicles light detection and ranging data imagery

AbstractDamage detection is essential for the maintenance of transportation infrastructure that experiences high daily traffic levels in potentially extreme environments and changes in use patterns. However, traditional physical inspection is always labor‐intensive, subjective, and biased, lacking the objective perspective required for a comprehensive and reliable assessment. Recently, unmanned aerial vehicles (UAVs) combined with emerging high‐performance sensor(s) have been intensively researched. Here, we present an aerial bridge surface survey method that can be used to assess damage. Existing damage detection methods focus on single types of damage and are limited in locating global damage, whereas our method detects two types of damage on the surface and marks them in a panoramic image. The workflow involves three steps: data acquisition using a meticulous UAV flight strategy that covers the entire surface, data processing using image‐based and point‐cloud models after polynomial rectification, and data output (i.e., damage detected by the combined models). To verify the method, a field test detected damage to two real bridges. A UAV equipped with a camera and light detection and ranging (LiDAR) equipment was employed. Experiments demonstrate the effectiveness of the proposed method, which is capable of producing accurate outputs and detecting damage with an average position error of 13.37 mm and a relative size error of 25.25%. Owing to the data fusion model taking advantage of two‐dimensional (2D) images and 3D LiDAR data, it outputs a high‐resolution 3D model and avoids environmental disturbances. After decision‐making‐level damage fusion, all position and size properties of damage information are computed into a panoramic damage image. This panoramic image showing all detecting damage helps technicians perform maintenance; the image can be zoomed to focus on any issue individually.

Cultivating a harmonious soundscape in urban public space: An empirical study of sound and activities

This study examines the relationship between sound and activities in urban public spaces in an attempt to create a pleasant acoustic environment that improves the quality of activities conducted in such areas. The study collected data from park visitors in Bandung using field measurements and questionnaires. The findings indicate that sound sources have a more significant effect on visitors' participation in activities than the overall soundscape quality. Visitors would continue to engage in activities despite the high traffic noise levels as long as the appropriate sound sources are present. Additionally, the study identified that the Social-Nature Connection activities require a soundscape that is lower in background noise, has some of the natural sound components, and with the addition of music to provide some dynamic vibes. On the other hand, the Restorative Retreats activities show no relation with either sound sources or noise level, and Exploring Natural Landscapes activities are influenced positively by man-made sound, specifically recreational sound. This study provides valuable insights that may be used to improve the design of soundscapes in urban public spaces, enabling designers to create a more balanced acoustic environment that supports various activities and enhances the quality of visitors' experiences.

LTE/LTE-A Based Advanced Wireless Networks

LTE/LTE-A is a wireless broadband standard that provides quick and reliable connectivity for the Internet of Things (IoT) and other connected devices. It is the de facto standard for 4G wireless, offering high-speed communication, extensive network coverage, and low latency. LTE/LTE-A networks are crucial for real-time IoT applications, offering high-speed data transfer, extensive coverage, low latency, and scalability. However, challenges in evaluating LTE/LTE-A-based wireless networks for IoT include compatibility, cost, power consumption, network coverage, and security. Large-scale deployments are hindered by cost, power usage, real-time data transfer, security vulnerabilities, and interoperability. Network performance may be impacted by high data traffic levels, expensive setup and maintenance, and interference from other wireless devices. LTE/LTE-A networks are complex and require sophisticated network technologies and protocols, making them difficult for some IoT stakeholders to build and administer.

Statistical Analysis of Traffic Noise Status at Selected Junctions in Port Harcourt Metropolis

Traffic noise is one of the dominant forms of environmental pollution in most urban cities that adversely affect human health globally. The traffic noise emanating from motor vehicles has become a common health problem in many metropolitan cities in developing countries of the world. This study evaluated traffic noise at selected major junctions (Rumuola, Garisson, Boro Pack, and Lagos Bus stop) in Port Harcourt Metropolis. Traffic noise levels at four congested junctions and a control junction in the Metropolis were monitored using a digital sound level meter. Noise indices, L10, L50, L90 equivalent noise levels (Leq), noise climate (NC), noise pollution index (NPI); traffic noise index (TNI); noise pollution level (Lnp); day-evening-night equivalent metric (LDEN) and percentage highly annoyed (%HA) were statistically determined. Traffic noise at Rumuola junction showed traffic noise ranging from 51.9 to 107.9dBA with a mean deviation of 91.3±8.4dBA; traffic noise at Garrison junction ranged from 52.8 to 107.6dBA with a mean deviation of 88.5±9.7dBA; Boro Park junction showed traffic noise ranging from 48.9 to 106.4dBA with a mean deviation of 83.7±10.1dBA; Lagos Bus Stop junction ranged from 45.4 to 94.9dBA with a mean deviation of 81.5±10.8dBA; while the Control junction (Ibadan Street junction)showed a traffic noise ranging from 48.4 to 61.3dBA with a mean deviation of 51.6±5.3dBA. Noise levels at the studied junctions were significantly high and exceeded permissible limit compared to the control junction (p-value = 0.00485; 95%CI). L10 (94.8dBA), L50 (86.8dBA), L90 (76.1dBA) and Leq (92.4dBA) were highest at Rumuola junction and lowest at Control junction (with 57.3dBA, 52.8dBA, 48.4dBA and 54.1dBA, respectively). Computed NPI values (1.25-1.34) indicated high traffic noise levels at the four junctions and low (0.77) at the control junction; Lnp values (105.0-116.6dBA) indicated high traffic noise pollution at the four junctions and low (63.0dBA) at the control junction; TNI values (120.9-138.5) indicated high traffic noise impacts at the four junctions and low (54.0) at the control junction. Computed LDEN and %HA indicated high level of traffic noise annoyance to the four junctions. The study revealed high traffic noise pollution at the four junctions that may significantly affect public health and therefore requires further investigation by concerned authorities to assess the health effects of traffic noise on the surrounding residents and traders at the studied junction.

Analisis Subtitusi Limbah Plastik (LDPE) terhadap Karakteristik Marshall Pada Campuran Laston AC-WC

Waste which is a disposal material from production, both from nature and human activities that are not used, can cause heaps and piles of waste that some cannot be recycled, so that it can have a negative impact on society if it is not managed properly. Therefore, the authors use waste as a mixture in making laston or AC-WC. In this study used plastic waste type Low Density Polyethylene (LDPE) which is often found in the surrounding environment. The asphalt layer used is Laston Wearing Course (AC-WC) which is commonly used for high traffic levels. Variations in the levels of plastic waste used are 0%; 5%; 7.5%; 10% of the total weight of the asphalt plan. The stages in this research include the physical test of the material, checking the AC-WC specifications referring to the general specifications of Bina Marga 2018, and Marshall testing. The method used in this research is the wet method. The results of this study found the optimum asphalt content used as a mixture with the addition of LDPE plastic waste, namely 6.3% asphalt content. Marshall test results show a better level of stability than conventional asphalt. This can be proven by the results of testing using Marshall. the average stability value is 1,884,53kg. Where this value increases compared to the stability value in the mixture without the addition of LDPE which is 1,787,39 kg.Keywords: Asphalt Concrete Wearing Course, Low Density Polyethilene (LDPE), Marshall Parameters

Exploring potential of Marshall-RT as simple performance test to evaluate rutting resistance of asphalt mixtures

ABSTRACT This study explored a new simple monotonic Marshall rutting test (Marshall-RT) to evaluate the rutting resistance of asphalt mixtures. The Marshall-RT test setup combines the Marshall fixture (at the bottom) and the IDT fixture (at the top). The rutting resistance of asphalt mixtures was evaluated using peak load (Pmax) and work done for the deformation damage obtained from the load-displacement curve. Nine plant-produced asphalt mixtures having different types of binders (unmodified, crumb rubber modified binder (CRMB)), and polymer modified binder (PMB)) and gradations having different nominal maximum aggregate sizes (NMAS) were evaluated. The Marshall-RT test parameters (i.e. Pmax and W P m a x ) have shown a strong correlation with fundamental (i.e. Flow Number (FN)), simulative (i.e. Hamburg wheel tracking test (HWTT)), and simple monotonic (i.e. Ideal rutting test (IDEAL-RT)) rutting tests. Moreover, the Marshall-RT test has shown good repeatability, the highest differentiation potential, and consistent ranking with other rutting tests. Furthermore, for high traffic levels (i.e. 100 MSA (Million Standard Axle)), at 50°C preliminary minimum threshold criteria were proposed for Marshall-RT (Pmax and W P m a x ), and IDEAL-RT (RTIndex) as 5 kN, 14 kN-mm, and 90, respectively, to avoid premature rutting failure. Thus, the newly developed monotonic Marshall-RT test can also be used as a surrogate simple performance test to estimate the rutting potential of asphalt mixtures during the mix design and plant production phases as quality control (QC)/quality assurance (QA).

Decision trees and labeling of low noise pavements as support for noise action plans

Low noise pavements (LNPs) are a market driven trend to mitigate the high road traffic noise exposure levels. Their improvement towards acoustic efficiency and durability over time is a challenge since these factors can conflict with road primary functions, such as safety. LNPs are not always the most cost-effective solution in health effects prevention. Whilst Green Public Procurement (GPP) highlighted the importance of reducing rolling noise emissions by introducing new regulations for new-layed LNPs, the fixed minimum requirements are not exhaustive. Generally, limits are set following the Close ProXimity method, which is only source oriented. This method does not consider real traffic flows and it is not aimed at evaluating citizens’ disturbance. This work presents strategy tools that could assist policymakers in choosing LNPs, when truly effective, over other mitigations. The approach includes a variety of indicators that would allow for comparing different facets of noise assessment. The proposed methodology does not require additional efforts from stakeholders because the measurements required for the estimation of the indicators must already be carried out for both verification of legal limits and GPP. The strategy tools are a decisional tree to support the evaluation of the applicability of a LNP before its approval, and an evaluation flowchart applicable after its laying to evaluate its efficiency. Finally, a first LNP labeling approach, based on the same set of indicators, is proposed. As a case study, these tools are applied to measurements performed before and after the laying of twelve LNPs part of the LIFE NEREiDE project.

Optimization of asphalt cold recycling containing ordinary and waste additives based on life cycle assessment considering the road traffic level- case study: Coal preparation plant

In recent years, extensive research has been conducted on the use of second-hand or waste materials in the road pavement construction layers. Most of these studies evaluated the mechanical properties of materials and emphasized the environmental benefits of using waste materials for use in road construction projects, regardless of the environmental consequences. The present study intends to compare the life cycle of waste materials with standard materials and determine the optimal conditions for the selection of waste materials based on environmental criteria by considering life cycle assessment (LCA) and several environmental indicators. The analysis considered emulsified cold recycled asphalt with different types of activator fillers including cement, coal waste+lime and coal waste ash+lime. Also, the recycled pavement was compared with that of conventional asphalt pavement in this environmental assessment. The LCA analysis was performed for pavements with design traffic of 0.1–100 million equivalent single axle loads (ESALs). In order to design the pavements structure, 96 resilient modulus tests were done for 32 recycled mixes. Environmental indicators under study included energy consumption, abiotic depletion potential (ADP), global warming potential (GWP), acidification potential (AP), and eutrophication potential (EP). The collected data for the studied functional unit was undergone an environmental analysis in SimaPro software. Apart from a standard case, parametric study was accomplished to analyze the effect of activator additive content. Accordingly, it was concluded that for the standard case, the traffic level or in other words the highway grade is of the main importance criterion in choosing the rehabilitation method based on environmental indicators. Emulsified cold recycled pavement with waste additives can be environmentally justified only in projects with low to medium traffic levels of less than 5–10 ESALs. For projects with medium to high traffic levels, only the ordinary recycling method with cement was comparable to conventional reconstruction.

Use of rice husk ash as a supplementary cementitious material in concrete mix for road pavements

The present research analyzes the feasibility of using Rice Husk Ash (RHA) obtained as a residue from an industrial process as Supplementary Cementitious Materials (SCM) in a concrete pavement mix that meets the minimum requirements for a medium traffic level (NT2) road with reference to the General Road Construction Specifications of INVIAS (Colombia). For this purpose, statistical methodologies such as Composite Central Design (CCD), Response Surface Methodology (RSM), and a Multi-Objective Optimization were used to find an efficient mix design that meets the strength and workability criteria using the highest RHA content in partial replacement of cement. The design optimization results show that replacing 24.9% by weight of cement with RHA in a hydraulic concrete mix produces the highest flexural strength (4.2 MPa) of the combinations proposed in the composite central design. This strength could even be applicable for high traffic level (NT3) road, demonstrates that the use of RHA as SCM in concrete mixes for pavements may be feasible.