Road Traffic Volume Research Articles

Long Term Performance of Sustainable Concrete Pavement Preservation Strategies in Canada

Rigid pavement preservation and rehabilitation strategies for high traffic volume roads are important sustainable methods of extending the life of our concrete roadways. In 1989, the Ministry of Transportation of Ontario (MTO) undertook the rehabilitation of an exposed concrete pavement exhibiting various distresses. The existing pavement, originally constructed in 1963, consisted of 230 mm mesh reinforced Portland Cement Concrete (PCC) pavement with dowelled joints at a spacing of 21.3 m. The preservation strategies used on the northbound lanes, which had experienced moderate deterioration, consisted of using sustainable concrete pavement restoration (CPR) techniques, material specifications and construction methods, which included full depth repair, partial depth repair, diamond grinding and joint sealant replacement. The rehabilitation strategy selected for southbound lanes was a 180 mm thick plain jointed unbonded PCC overlay to address the severe 'D' cracking and spalling at all the joints and cracks. This paper will identify the sustainable concrete pavement preservation strategies using the pavement sustainability rating system – GreenPave. It will also discuss the pavement preservation strategies and their long term performance evaluation in terms of roughness measurements, frictional resistance measured, and pavement condition ratings. Overall, the 22 year performance of these preserved and rehabilitated concrete pavements has been good with acceptable levels of ride quality, frictional resistance and distress propagation.

The accumulation process of pollutants in deposited particles of different sizes on different roads in Beijing, China.

Road-Deposited Sediments (RDS) samples were collected from four different roads in Beijing, and the distribution of pollutants in RDS with various particle sizes was compared. In this study, the cumulative mass of RDS exhibited a positive correlation with the number of dry days, and the RDS load below 75μm was also influenced by road traffic volume. As traffic volume escalated, there was a corresponding increase in the load of these smaller RDS. Most pollutants accumulated within RDS with sizes below 150μm, rendering them the primary contributors to the pollution. In terms of the antecedent dry-weather days, fifteen days emerged as a potentially pivotal point, with both the rate of pollutant accumulation and the contribution of pollution sources to RDS having stabilized after this duration. The origins of pollutants in roads of different functional areas exhibited certain disparities. The pollutants on major roads with high traffic volume were attributed to frequent vehicular activities. The pollutants on residential roads stemmed from soil particles and fallen leaves in the roadside green belts as well as from human activities. And the pollutants on urban-rural crossroad might be attributed to the industrial contamination with factories located on one side.

VALUATING THE IMPACT OF URBAN ROAD TRANSPORTATION ON LAND USE PATTERNS IN GBAGADA LAGOS STATE

This study investigates the relationship between urban road transportation and land use patterns in Gbagada Lagos state. Using a mixed-methods approach combining Geographic Information System (GIS) analysis, survey questionnaires, and regression modeling, this research examines how road network density, traffic volume, and transportation modes influence land use changes. The findings reveal significant correlations between road proximity, land value, and urban sprawl. Specifically, areas with high road density exhibit increased commercial and residential development, while areas with limited accessibility experience decreased land value and reduced development. Policy recommendations include optimizing transportation infrastructure, promoting mixed-use development, and implementing smart growth strategies to mitigate urban sprawl and enhance sustainable land use. In particular, certain transportation planning decisions tend to increase sprawl (dispersed, urban fringe, automobile-dependent development), while others support smart growth (more compact, infill, multimodal development). These development patterns have various economic, social, and environmental impacts. This report describes specific methods for evaluating these impacts in transport planning.

A Study on selection of general national road traffic volume survey section criteria

A Study on selection of general national road traffic volume survey section criteria

PENGARUH VOLUME KENDARAAN TERHADAP KERUSAKAN JALAN PADA RUAS JALAN LEMBAR SELATAN - KEBUN AYU

Roads are an important factor in ensuring continued comfort and safety for all motorists, based on observations in the field, the condition of the South South Sheet crossing road to Kebun Ayu, which is approximately 5.7 km long, needs to be taken seriously and handled seriously by the government because the condition of the road has many potholes and bumps. The aim of this research is to determine the effect of vehicle volume on the level of road damage, and to determine the relationship between vehicle volume and the level of road damage on flexible pavement. This research is a case study research on the South South Sheet crossing road to Kebun Ayu. The data used in this research is secondary data such as road data and traffic volume data obtained from the West Lombok Regency Bina Marga service. Meanwhile, primary data obtained directly in the field includes vehicle volume data recorded during peak hours. The results of field data analysis showed that the road damage value (Nr) on the Southsheet – Kebun Ayu road was obtained with an average value (Nr) of 68.2; The traffic volume at peak hours based on passenger car units (pcu/hour) on the Kebun Ayu – South Sheet road is 560 pcu/hour, and in the South South Sheet - Kebun Ayu direction it is 546 pcu/hour. The equation for traffic volume analysis related to the value of road damage and time is Y = 0,025 X1 + 0,101 X2 + 25,74 with the magnitude of R2 or the correlation between variable x and variable y of 0.86 or 86%

Enhancing road safety with the infrastructure-adaptable NDBA 2.0 concrete median barrier: An Italian experience

Road safety is a crucial global concern because of the high number of fatalities and injuries resulting from road crashes each year. Median crossover collisions are among the most dangerous crashes that happen on highways, frequently leading to serious or fatal injuries. The main approach to decreasing the occurrence of these types of crashes is the installation of median barriers. When the need for such installations arises, road agencies must choose from various options, including concrete barriers, cable barriers, or metal-beam guardrails. This paper is dedicated to the New Dynamic Barrier for Highways (NDBA 2.0), an innovative technology for median barriers developed by the Italian National Road Agency (ANAS), emphasizing its pivotal role in enhancing road safety. It incorporates high-tensile steel and advanced composites, offering robust protection while maintaining a lightweight profile. What distinguishes the NDBA 2.0 is its dynamic nature, featuring an intelligent system that seamlessly adapts to the road infrastructure. Its modular construction, with sections of only 200 cm, allows for easy installation and ensures compatibility across successive road segments. This adaptability reduces construction time while maintaining the highest standards of performance. From a road safety perspective, the NDBA 2.0 offers substantial advantages. Its design contributes to minimizing crash-related costs by reducing the severity of crashes, particularly in the transition zones. The barrier's design allows it to adapt to varying road conditions and traffic volumes, effectively addressing common installation challenges on existing roadways as well. Its ability to be directly supported on the road surface wear layer eliminates the need for costly foundation structures, facilitating quick installation and reducing maintenance expenses. The NDBA 2.0 barrier was designed to eliminate the need for future simulations in the design and verification of transitions between different barriers. For this reason, the NDBA 2.0 barrier has been tested in real-world conditions in class H4 and, consequently, is equipped with CE marking. This study offers a comprehensive analysis of the NDBA 2.0 barrier, whose implementation may provide significant benefits for road safety. Continued research, collaboration, and widespread adoption of the NDBA 2.0 barrier can further enhance road safety on a global scale.

Optimization Method for Allocating Peak-Period Parking Demand in Hub Parking Lot Clusters

With the expansion of urban scale and the popularization of multi-modal transportation, transportation hubs, as the link of multi-modal travel, are becoming increasingly important in urban development and residents’ lives. In situations of high parking demand, the increase in road traffic volume and parking search delays exacerbates the service pressure on hub parking lots and the traffic congestion on surrounding roads. Therefore, reasonable parking demand allocation is one of the key solutions to this problem. Based on the analysis of the vehicle parking search process, this paper constructs a model for estimating parking search delay on roads outside hub parking lots and proposes an optimization model for parking demand allocation aimed at minimizing the total parking search delay of vehicles. Finally, taking a major transportation hub in Nanjing as a case study, data were obtained through field investigations and simulation experiments to identify peak parking demand periods and calibrate the model parameters. The results show that the average vehicle delay was reduced by 4.5%, with a total reduction of 13,860 s in vehicle delay for parking demands at the hub within one hour. Therefore, by optimizing the allocation of parking demand, the average delay for vehicles searching for parking can be reduced to a certain extent.

Analyzing Energy Efficiency and Battery Supervision in Electric Bus Integration for Improved Urban Transport Sustainability

Addressing the critical challenge of reducing local emissions through the electrification of urban public transport, this research specifically focuses on integrating electric buses. The primary objectives are to evaluate energy efficiency and ensure battery cell supervision. Introducing electric buses plays a significant role in reducing emissions, contributing to more sustainable urban transport systems. However, this transition introduces a set of new challenges, including the complexities of electric charging logistics, the establishment of new consumption standards, and the intricate relationships between distance traveled, ambient temperature, passenger load, and battery health. Methodologically, this study collects and examines factors impacting energy consumption, including external temperatures, bus conditions, road conditions, and driver behavior. By analyzing these variables, a baseline for actual consumption can be established, allowing for the calculation of an energy balance to identify energy inefficiencies. This enables the optimization of route planning, the strategic selection of stops, and the efficient scheduling of charging times, along with ensuring the proper scaling of the bus battery system. This study found that energy consumption peaked at 116.73 kWh/100 km in the lowest temperature range of −5 °C to 0 °C. Consumption decreased significantly with rising temperatures, dropping by 25 kWh between 5 °C and 10 °C and by an additional 10 kWh between 10 °C and 15 °C. Beyond 20 °C, variations were more influenced by route and driving style than by temperature. Route and driver variability significantly influenced energy consumption, with up to threefold differences across routes due to factors such as road type and traffic volume. Additionally, there was a 31.85% difference between the most and least efficient drivers, highlighting the critical impact of driving style. Furthermore, this study explores the assessment of battery systems through cell-level diagnostics to detect potential faults. Considering that buses are equipped with significantly more batteries than typical electric vehicles, detecting and localizing faults at the cell level is crucial to avoid the substantial costs and environmental impact associated with replacing large battery systems. Utilizing the results of this research and the applied examination methods, it is possible to enhance energy efficiency and extend battery life, thereby contributing to the development of more sustainable and cost-effective urban transport solutions.

Brick dust and fly ash as subgrade stabilizer for Low Traffic Volume Roads: laboratory and test track evaluation

Brick dust and fly ash as subgrade stabilizer for Low Traffic Volume Roads: laboratory and test track evaluation

Assessing Roller Compacted Concrete using GGBS as Partial Cement Replacing Material for Application in Low Traffic Volume Road

This paper reports most optimized mix derived from the roller compacted concrete (RCC) using ground granulated blast furnace slag (GGBS) as the partial cement replacing materials in the context of possible utilization of RCC in the construction of rigid pavements in the rural part of the country, especially subjected to low vehicular traffic volume. In the current study, various RCC mix compositions were developed by substituting ground granulated blast furnace slag (GGBS) for ordinary Portland cement (OPC) in varied percentages (0%, 20%, 40%, and 50%) and assessed for mechanical (strength) properties. All the three GGBS blended mix compositions are found to give early age compressive strength more than 20 MPa and 28 days compressive strength more than 30 MPa. Further, they are found to have split tensile strength in the range of 2.8-4.1 MPa. Moreover, they are found to yield the flexural strength more than 3.8 MPa. All the three mixes are found to comply with the requirements of compressive strength, splitting tensile strength and the flexural strengths as prescribed by Indian Roads Congress Specification and American Concrete Institute Standards for possible utilization in the construction of rigid pavements in the rural parts of the developing country like India. Further, the strength values of the GGBS blended mixes increases from 20% to 40% and decreases thereafter, at the higher GGBS contents such as 50%. In view of this, the RCC mix composition with 40% GGBS contents can be regarded as the most optimal mix to be used in the construction of rigid pavements in rural part of the country.

Developing accident frequency prediction models for urban roads: A case study in São Paulo, Brazil

The growing number of vehicles and the evolving behaviour of road users present new and additional challenges to road safety. Study on the variables that influence the frequency of crash occurrences such as road geometry, junction, speed and land use are needed as they have proven effects on the number and severity of crashes. In this paper, we identify and assess the variables, namely road geometry, vehicle speed, traffic volume, land use and junction type, and develop accident frequency prediction models for a main urban transport corridor in São Paulo, Brazil. Crash data was provided by the traffic management company of the city, other datasets were obtained from a mix of primary and secondary sources including roadside cameras, Geographic Information Systems (GIS) and digital mapping tools. The studied road was segmented and the coefficients associated with variables in the segments were obtained using Poisson regression through a stepwise variable selection procedure. Two models with junctions density per type (access/km, T-junction unsignalised/km, T-junction signalised/km and crossroads/km) and junction density per merged type (signalised/km and unsignalised/km) along with land use per type (commercial and residential) are developed. The junction density and land use are found to be significant and positively correlated with crash frequency. The models were evaluated by statistical means for their accuracy of predicting the crashes, and validated with additional information obtained from field observation.

Simulation-Oriented Analysis and Modeling of Distracted Driving

Distracted driving significantly affects the efficiency and safety of traffic flow. Modeling distracted driving behavior in microscopic traffic flow simulation is essential for understanding its critical impacts on traffic flow. However, due to the influence of various external factors and the considerable uncertainties in behavior characteristics, modeling distracted driving behavior remains a challenge. This study proposed a model which incorporates distraction features into the microscopic traffic flow model to simulate distracted driving behavior. Specifically, the study first examines the characteristics of distracted driving, including the intervals and durations of distraction events, as well as the patterns and environments of distraction. It then introduces distraction parameters into the Intelligent Driver Model (IDM), including reaction time delays and perception deviations in both speed difference and following distance. These parameters are quantified by probabilistic distributions to reflect the uncertainty and individual differences in driving behavior. The model is calibrated and validated using 772 distracted following events from the Shanghai Naturalistic Driving Study (SH-NDS) data. Three patterns of distraction (excessive, moderate, mild) are distinguished and modeled separately. The results show that the model’s accuracy surpasses that of the IDM under various road types and traffic volumes, with an average improvement in model accuracy of about 11.30% on expressways with high traffic volume, 4.54% on expressways with low traffic volume, and 4.46% on surface roads. Meanwhile, the model can effectively simulate the variations in reaction times and perceptual deviations in both speed and following distance for different distraction modes at the individual level, maintaining consistency with reality. Finally, the study simulates distracted driving behavior under different road environments and traffic volumes to explore the impact of distracted driving on traffic flow. The simulation results indicate that an increase in the proportion of distraction reduces the efficiency and safety of traffic flow, which is consistent with real-world observations. Since the model considers human distraction factors, it can generate more dangerous driving scenarios in simulations, which holds significant importance for safety-related research. The findings from this study are expected to be helpful for understanding distracted driving behavior and mitigate its negative influence on the efficiency and safety of traffic flow.

Comparative Sensitivity Analysis on Intersection Crash Prediction Models by Control Type: Highway Safety Manual Approach

A comprehensive, in-depth investigation into the comparative safety of different intersection control types is presented, specifically signalized and minor road stop-controlled intersections across facility types. Employing a rigorous sensitivity analysis, the study scrutinizes intersection crash prediction models (CPMs) rooted in the Highway Safety Manual (HSM) methodology. Through meticulous data analyses and thorough comparisons of predictive models across a range of major and minor road traffic volumes, the paper critically examines the portrayal of signalized and stop-controlled intersections within the default HSM Part C CPMs. Additionally, the study delves into the effects of certain crash modification factors on CPMs, further exploring the impacts of calibration factors and locally developed models on crash prediction results. CPMs for signalized intersections do not uniformly lead to fewer crashes compared with stop-controlled intersections, especially under certain traffic volumes and when considering fatal and injury crashes. Therefore, the choice of intersection control should be based on more nuanced criteria than traffic volume alone. Additionally, the research emphasizes the role of intersection geometry and operations, for example, the benefits of adding turn lanes and varying left-turn phasing, in influencing safety outcomes. This study significantly contributes to the understanding of intersection safety and HSM modeling approaches, providing a valuable resource for transportation professionals dedicated to advancing intersection safety. Examining strengths and limitations of existing models provides valuable input for researchers developing future intersection CPMs, and offers essential insights for transportation planners and engineers, informing decision-making for optimizing intersection control strategies and enhancing overall intersection safety and traffic management.

Daily motor vehicle traffic volume and other risk factors associated with road deaths in U.S. counties

Introduction: Road death risk is often characterized as deaths per volume of traffic in geographic regions, the denominator in miles or kilometers supposedly indicative of the magnitude of risk exposure. This paper reports an examination of the differences in the predictive value of factors hypothesized to influence traffic volume and road death risk. Method: The association of 11 risk factors in U.S. counties during the first 7 months of 2020 was examined for consistency of predictions of road death and traffic volume measured by cell phone and vehicle location data. The study employed least squares regression for traffic volume and Poisson regression for deaths with the population as the offset variable. Results: The directions of the regression coefficients for traffic volume and odds of road deaths per population were opposite from one another for 9 of the 11 variables in the analysis of vehicle occupant deaths. Only the coefficients for maximum daily temperature and Saturday travel were in the same direction. The confidence intervals of three risk ratios for pedestrian deaths indicated low reliability but most of the predictor variables were opposite in association with traffic volume and odds of death. Although traffic volume plunged in the first weeks of the pandemic, the results for the months before and during the COVID-19 pandemic were similar. Practical applications: Traffic volume is an inverse risk factor for road deaths at the local level, likely the result of lower speeds on congested roads. Without the application of countermeasures aimed at reducing speed and other risk factors, the reduction of road congestion is likely to increase deaths.

Safety Assessment of Suburban-Type Arterial Roadways: New Findings Using Heterogeneity Models

This study investigates the safety performance of suburban-type roads (STRs), a category of medium-speed arterial roads characterized by high vehicular traffic and limited pedestrian and cyclist mobility. Such roadways present unique challenges in road safety, often overlooked in traditional road design focused predominantly on driver needs. By employing a correlated random parameter ordered probit model to analyze police-reported crash severity data from STRs, this research uncovers critical insights into the factors influencing crash injury severities on these roads. Our findings highlight the nuanced impact of various dimensions, such as road design, traffic volume, and environmental conditions, on STR safety; the results offer a detailed understanding of crash contexts on STRs and point toward targeted interventions for enhancing road safety. These interventions include the potential redesign of roadways to accommodate diverse user needs and the implementation of speed regulation measures tailored to specific road characteristics. This research contributes significantly to the existing body of knowledge on suburban road safety, providing evidence-based recommendations for improving the overall safety of these increasingly prevalent road types. The implications of these findings are far-reaching, offering a foundation for future studies to explore diverse methodologies in road safety analysis and to extend this research to other geographic contexts.

Wildlife mortality risk posed by high and low traffic roads.

Wildlife mortality due to collisions with vehicles (roadkill) is one of the predominant negative effects exerted by roads on many wildlife species. Reducing roadkill is therefore a major component of wildlife conservation. Roadkill is affected by various factors, including road attributes and traffic volume. It is theorized that the effect of traffic volume on roadkill probability should be unimodal. However, empirical evidence for this theory is lacking. Using a large-scale roadkill database of 18 wildlife species in Israel, encompassing 2846km of roads over 10years, we explored the effects of traffic volume and road attributes (e.g., road lighting, verge vegetation) on roadkill probability with a multivariate generalized linear mixed model. A unimodal effect of traffic volume was identified for the striped hyena (Hyaena hyaena), whereas 5 species demonstrated a novel quadratic U-shaped effect (e.g., golden jackal [Canis aureus]). Four species showed a negative linear effect (e.g., wild boar [Sus scrofa]). We also identified varying effects of road attributes on roadkill. For instance, road lighting and roadside trees decreased roadkill for several species, whereas bus stops and concrete guardrails led to increased roadkill. The theorized unimodal effect of traffic volume may only apply to large, agile species, and the U-shaped effect could be related to intraspecies variability in traffic avoidance behavior. In general, we found that both high-traffic and low-traffic roads can pose a high mortality risk for wildlife. It is therefore important to monitor roadkill on low-traffic roads and adapt road attributes to mitigate roadkill. Road design for effective roadkill mitigation includes reducing the use of concrete guardrails and median barriers where possible and avoiding dense bushes in verge landscaping. These measures are complemented by employing wildlife detection systems, driver warnings, and seasonal speed reduction measures on low-traffic roads identified as roadkill hotspots.

Determining Priorities for Handling Environmental Road Sections in Palu City (Case Study in West Palu District)

Palu City has numerous roads, including environmental road networks, where the function of many environmental roads has decreased due to heavy traffic and damaged road structures. The improvement of environmental road infrastructure is a complex issue that requires objective policymakers. Sometimes, the work carried out to address environmental issues on roads is not prioritized effectively. To tackle this problem, a research study was conducted to determine the priority order for handling environmental roads in the West Palu sub-district of Palu City. The study used a multi-criteria analysis approach to determine priorities, where the criteria were weighted based on input from respondents from government agencies related to road infrastructure. The criteria used to determine priorities in this research were road conditions, traffic volume, land use, and development planning deliberation proposals. The criteria for road conditions and traffic volume were given the highest priority weighting with weight values of 39.10% and 28.10%, respectively. This was followed by the development planning deliberation proposal criteria at 21.50% and land use criteria at 11.30%. By weighting criteria and scoring criteria based on operational criteria variables, the analysis obtained the top 5 priority orders for handling environmental road sections on Jl. Srikaya. Lr. Sirsak II Kel. Kamonji, Jl. Mas Mansyur Lr. Kel. Baru, Jl. Samudra II Lr. II Kel. Lere, Jl. Lasoso Lr I Kel. Lere and Jl. Durian Lr. Kel. Kamonji.

Managing Landscape Urbanization and Assessing Biodiversity of Wildlife Habitats: A Study of Bobcats in San Jose, California

In the rapid process of urbanization, crucial habitats for mid-sized felids such as bobcats are increasingly compromised. This study employs Geographic Information System (GIS) tools and Machine Learning to investigate the subtle impacts of urbanization on bobcat habitats. Focused on the San Jose area, our extensive geospatial analysis has developed a complex ecological model for bobcat habitats. Our findings emphasize the significant influence of factors like vegetation cover, water body distribution, road traffic volume, and intersection density on the suitability of habitats for bobcats. Specifically, we discovered that while vegetation cover typically supports habitat suitability, its proximity to busy roads significantly undermines this advantage, indicating a need for strategic urban planning that incorporates wildlife mobility. By synthesizing natural and urban elements, we offer fresh insights into urban ecosystem management and propose specific conservation tactics: identifying optimal wildlife crossings, integrating corridors with urban infrastructure, and placing fencing and signage strategically to facilitate wildlife movement safely. These measures aim to reduce road-related threats and enhance the integrity of natural habitats, strengthening bobcat conservation efforts. More than its direct implications for bobcat conservation, this study offers actionable insights for urban wildlife conservation and introduces innovative methods for assessing and mitigating the broader ecological impacts of urbanization.

Analysis of The Feasibility of Revitalization of The Type a Amplacing Terminal and The Performance of The Sisingamangaraja Road Section, Medan

The main objective of this research is to analyze and find out if the investment plan is profitable in the future so that it is feasible or not to be implemented. Apart from that, this research also aims to analyze the Operational Performance of the Sisingamngaraja Road Section which includes: Side Obstacles, Free Flow Speed, Travel Speed and Time, and Service Level. The data used in this research are primary data and secondary data. Primary data was obtained through interviews and observations. Meanwhile, secondary data was obtained from related agencies or services such as the Medan City Transportation Department. The analytical method used in this research uses two analytical tools, namely investment feasibility analysis and road segment performance analysis. The research results obtained from the Net Present Value for the next 10 years are IDR. 60,400,000. shows that it is feasible to revitalize the Amplas Type A Terminal. This can be proven from the investment acceptance criteria and the NPV method, namely if the calculation results show that the value is positive then the investment is worth implementing. From the calculation results, the IRR of 30.5% shows that the interest rate will equal the present value of the investment. With present value, the value of net cash receipts in the future. As a criterion for acceptance of this method, if the calculated interest rate is greater than the desired interest rate, the investment is accepted. In this case the interest rate is 20%, so the IRR of 30.5% is said to be feasible for the revitalization of the Amplas Type A Terminal. The Profitability Index (PI) is 1.10 (accepted) because PI > 1. From the results of the Payback Period calculation, the Payback period for the revitalization of the Amplas Type A Terminal is 22.2 years. This means it is shorter than the economic investment period, namely 35 years, so the Payback Period criteria for the revitalization of the Amplas Type A Terminal can be accepted because it is lower than the useful life period. The performance of the section on Jalan Sisingamngaraja by determining the size of the road capacity and traffic volume is known to still have problems with congestion during peak activity hours.

An optimisation-based digital twin for automated operation of rail level crossings

Railway level crossings (LCs), as the intersection of road and rail transport, are the weak points in terms of safety, as they are used by different modes of transport. The safety level at LCs can therefore be affected by the behaviour of the users. However, the level of safety can also be affected by failures and errors in the operation of LC equipment. Apart from safety, errors and failures of the LC devices can lead to longer waiting times for road users. As the volume of traffic on rail and road increases, so does the risk that the level of safety will decrease. The increase in traffic volume via LC leads to higher traffic volume on the road and more frequent trains on the rail, which leads to longer waiting times for road users on the LCs. The longer waiting times can disrupt the traffic flow, especially during peak hours when the growing volume of traffic on road and rail increases road user dissatisfaction. Moreover, in the era of Industry 4.0 and Digital Rail, new digital and automated technologies are being introduced to improve rail performance and competitiveness. These technologies are aligned with the LCs and are intended to ensure the efficient operation of LC and the efficient use of LCs by conventional trains as well. To achieve this, a concept is needed that simultaneously monitors and visualises the operation of LC in real time, identifies potential faults and failures of the LC equipment, and updates and monitors the proper operation of LC based on the historical data and information of the operation of LC according to the road traffic volume and the characteristics of the rail traffic and trains. Therefore, in this study, a digital twin system (DT) for rail LC was initiated and built as a concept that can meet the above requirements for proper LC operation in real time. DT of LC includes all components of LC and communication between them to synchronise the operation of LC according to the real-time requirements. The DT system is able to optimise the operation time of LC by monitoring the operation of LC and collecting data to ensure efficient use of LC and reduce unnecessary waiting time for road users. In this paper, the operation time of LCs on Swedish and Taiwanese railways was compared using the developed level crossing optimisation model (OLC). Since the introduction of new signalling concepts requires an improvement of LC operating characteristics and their design, the operating strategies were modelled using the OLC model. The results of the work show that the optimal values of LC operation time are different for the case studies investigated. The replacement of track circuits as detection devices and the introduction of balises can also positively influence the operation time, as well as increasing the speed of trains via LCs. However, due to the formulation of the OLC model, the impact of a longer train length on the operation of LC is not recognised. The OLC model can be used to estimate the real-time operation time of LC under different traffic conditions as well as the impact of different changes and extensions of LC.