Nevada Department Of Transportation Research Articles

SENE: A novel manifold learning approach for distracted driving analysis with spatio-temporal and driver praxeological features

Although there are many studies conducted on distracted driving, the growing number of accidents on roads demands further serious attention. The majority of the distracted driving-related data in real life are unlabeled and higher dimensional, leading to complex analyses. There is a lack of existence of proper indices for understanding the perilousness due to distracted driving, which makes it very difficult to understand which road or neighborhood has a higher risk of accidents. Despite earlier studies have focused on either spatiotemporal or praxeological factors separately, they have not considered both factors together. Moreover, crisp rule extraction and interpretation are lacking in the literature. Therefore, to deal with such issues, we have proposed a new methodology which: (i) develops Schrodinger Eigenmap Neighborhood Embedding (SENE) manifold learning for dimensionality reduction, followed by K-means clustering, (ii) develops road perilousness index (RPI) and neighborhood PI (NPI) to explain dangerousness of roads or neighborhoods, (iii) uses both spatiotemporal and driver praxeological factors, and (iv) develops Tolerance Rough Set Approach (TRSA) for crisp rules generation and interpretation. Road accident data from the Nevada Department of Transportation is used as a case study. Besides, a total of four benchmark datasets from the University of California Irvine repository are also used for comparative study to prove the superiority of our proposed methodology over some state-of-the-art. Experimental results reveal that the proposed methodology outperforms others by providing the highest clustering accuracy with four clusters. Finally, a set of 16 crisp rules are extracted and interpreted from clusters using TRSA.

Improving snow plowing safety and efficiency using computational and experimental approaches: Rear side of snow plow truck

The main objectives of this study were to explore the means of reducing or eliminating snow build-up on rear warning lights and snow cloud in the wake of snowplow trucks during high-speed snowplowing (HSSP). These snow build-up on rear surfaces and snow cloud in the wake zone cause serious safety and efficiency problems due to diminishing visibility for the following motorists and amount of time needed to clear snow off from rear surfaces of snowplows. Furthermore, research and studies were carried out to solve the visibility problems experienced by the State of Nevada Department of Transportation (NDOT) snowplow trucks. Fluent 6.3.26 and ANSYS Fluent 12.1 Computational Fluid Dynamics (CFD) were utilized, and field tests were conducted with the mechanical design methods which were feasible and compatible with the snowplow trucks. Previously designed and installed rear foil (airfoil) helped reducing snow accumulation on most of the rear surface of truck except the right taillight. However, its effect in reducing snow cloud in the wake of the truck was limited. In this study several new designs were developed computationally including modifications on the current airfoil design. Based on computational (CFD) results, two of these designs were constructed and tested on NDOT trucks during routine HSSP. Preliminary test results showed promising results. Design process and test results are discussed in this paper.

Addressing Driving Actions of At-Fault Older Drivers: Bayesian Bivariate Ordered Probit Analysis

This study aimed to examine the driving actions of at-fault older drivers, and investigate the interrelations between the unobservable factors. To reach the goal, a Bayesian bivariate ordered probit model was proposed, which addressed the driving actions of different drivers simultaneously, and accommodated the interrelations between the unobservables by covariance. The data with 27 arterials from 2014 to 2017 were collected from ArcGIS open data site maintained by Nevada Department of Transportation (NDOT). Compared to individual Bayesian random parameter ordered probit model, the proposed model outperformed according to goodness-of-fit. Results revealed that injury severity and total vehicles were potentially significant factors for actions of at-fault older drivers, while total vehicle and vehicle condition were significant for actions of not-at-fault drivers. The findings can provide potential insights for practitioners to apply the new technology and remind the driving actions of older drivers.

Improving snow plowing safety and efficiency using computational and experimental approaches: Front side of snow plow truck

The main objectives of this study are improving snowplow truck operator's visibility, especially under heavy and deep high speed snowplowing (HSSP), and explore the means of reducing or completely eliminating engine overheating due to snow blocking the air flow to radiator. During HSSP, snow (from roadways) may overflow the moldboard, and can cause snow accumulation on truck windshield that reduces snowplow operator's visibility. Snow overflowing the moldboard can also cause snow and ice accumulation on engine radiator grille that originate engine overheating problem by blocking the airflow to radiator. Research and studies are carried out to solve the problems of State of Nevada Department of Transportation (NDOT) snowplow trucks. Computational Fluid Dynamics (CFD) studies are utilized to design a moldboard overplow deflector. Snow particles are computationally studied using the Discrete Phase Modeling (DPM) to analyze their trajectories after particles bounce back from the plow moldboard and truck. Resulting deflector is manufactured and it is mounted over the moldboard of one of the NDOT Trucks serving the Mount Rose area in western NV. Field tests, and experiments were promising and showed considerable reduction in snow accumulation on the engine grille, and truck windshield.

Method to estimate design resilient modulus (Mr) of unbound materials for rehabilitation in M−E design

The resilient moduli (Mr) of the unbound layers and subgrade (SG) soils play a major role in estimating the pavement responses and analyses for mechanistic-empirical (M−E) pavement design. Most of the analysis procedures require a single representative Mr value for each unbound layer. However, estimating one representative values for each unbound layer is difficult as it depends on the state of the stresses within the layer. In this study, the stepwise mechanistic analysis approach is used for determining representative Mr values for the unbound materials typically used in Nevada. The Nevada Department of Transportation (NDOT) uses mainly three types of unbound material in the pavement structure; crushed aggregate base (CAB), borrow material, and SG soils. The unbound materials were sampled from multiple locations throughout Nevada District 1 and evaluated through several laboratory tests, which include sieve analysis, moisture-density relationships, and resilient modulus. The resilient modulus values for unbound material at multiple states of stresses were measured in accordance with AASHTO T307. The measured resilient modulus values were fitted to multiple constitutive models to assess the suitability of the models. The CAB and borrow materials fit the theta model very well while the SG soils fits the Uzman model and universal model. The ILLI-PAVE 2005 finite element (FE) program was employed for computing stresses as well as deflection basins in typical conventional flexible pavements under a representative tire loading. The calculated deflection basin was used for estimating the Mr values of the unbound layers using MODULUS 6.1 software.

Evaluation of the benefits of open graded friction course: Case study

This study evaluated the benefits of Open Graded Friction Course (OGFC) via two field projects constructed by the Nevada Department of Transportation: one project was in Elko, and the other was in Las Vegas. Each project included both the OGFC and Dense-Graded Hot Mix Asphalt (DGHMA) sections. The Elko project was located in the town area of Elko while the Las Vegas project was constructed in a rural area on I-15 interstate highway. Laboratory tests were performed to evaluate the durability, rutting, and moisture-susceptibility of OGFC mixtures. The selected test methods included the Cantabro test, Tensile Strength Ratio test, and Hamburg Wheel-Track test (HWTT). The laboratory test results showed that the Las Vegas OGFC mixture passed all the performance criteria, but the Elko Mixture failed to satisfy the HWTT criterion.The field performance tests were conducted to assess the permeability, friction, and noise functionality over time. The selected test methods included the NCAT falling head permeameter test, locked-wheel skid trailer test, and On-Board Sound Intensity test. The field performance results demonstrated that the Las Vegas OGFC pavement exhibited benefits in permeability, friction, and noise reduction compared to the DGHMA pavement, while the Elko OGFC pavement showed comparable performance with the DGHMA pavement after 2-years of service. Finally, a cost-benefit analysis was conducted to monetize the advantages and disadvantages of OGFC pavements. As demonstrated in the economic analysis, the OGFC pavement in Las Vegas reduced the net present value of OGFC costs by 36%, while the OGFC pavement in Elko increased the net present value of costs by 86%. This indicates that the implementation of OGFC is cost-effective in rural highways but impractical in urban or town areas. High speed traffic is generally needed to help keep the interconnected voids of an OGFC pavement from becoming clogged over time. As a result of the reduced speed on the Elko project, the permeability functionality was lost after one year and the noise reduction benefit was lost after thirty two months.

Statistical Distributions of Pavement Damage Associated with Overweight Vehicles: Methodology and Case Study

The trucking industry is the primary mode of transporting for goods and commodities in the United States. Currently, there is an increasing trend in the use of overweight (OW) vehicles on the highway network. State highway agencies (SHAs) are challenged to address this increase, particularly relative to associated pavement damage. In this study, a probabilistic method was developed to evaluate rutting and fatigue cracking damage caused by OW vehicles under different road and environmental conditions. The influential input parameters in this analysis included gross vehicle weight (GVW), axle configuration, axle weight, pavement temperature, and vehicle-miles traveled (VMT). Necessary information was obtained by analyzing more than 170,000 entries of a Nevada Department of Transportation (NDOT) OW permit database. The developed model was based on mechanistic-empirical (ME) approach and considered asphalt concrete (AC) viscoelastic characterization. The results of this study were distributions of AC critical responses, load equivalency factors (LEFs), and relative damage factors (RDFs). The analysis showed that load equivalent factor (LEF) distributions could be incorporated in pavement design methods to account for OW vehicles. Furthermore, the damage induced by specific OW vehicles could be assessed using the relative damage factor (RDF) concept and may be efficiently used by SHAs during the permit application process. A case study was presented illustrating the impact of an OW axle configuration on pavement damage. Finally, a method was suggested for developing RDF tables with damage ranges corresponding to different axle configurations and the GVW that could be a tool for SHAs to evaluate and understand pavement damage induced by OW vehicles.

Wind speed and wind direction forecasting using echo state network with nonlinear functions

Abstract Wind turbines are among the most popular sources of renewable energy. The energy available from wind varies widely because wind energy is highly dependent on continually fluctuating weather related parameters such as wind speed and wind direction. Wind farms have difficulties with system scheduling and energy dispatching because the availability of wind power is not known in advance. Therefore, the growth of wind power penetration in the emerging power system has made a precise wind forecasting method indispensable for system operators to include wind power generation in unit commitment and economic scheduling. This paper proposes two methods for wind speed and direction forecasting based on the nonlinear relations between the internal states of echo state networks. The methods decrease the number of internal states, and reduce the computational load compared to classical ESNs with fixed sizes and topologies by reducing the orders of the weight matrices. The design is simple with high learning capability and prediction accuracy, and does not require extensive training, parameter tuning, or complex optimization. The methods are tested with wind speed and direction data provided by the Nevada department of transportation (NDOT) roadway weather stations in the Reno, NV area. To demonstrate the efficiency of the proposed methods, they are compared with classical echo state networks (ESN) and with adaptive neuro-fuzzy inference system (ANFIS). The results of the new methods compare favorably with both ESN and ANFIS.

Damage Assessment for ME Rehabilitation Design of Modified Asphalt Pavements: Challenges and Findings

The overall objective of this study was to assess the use of Level 1 analysis for mechanistic-empirical (ME) rehabilitation designs of deteriorated polymer-modified asphalt concrete (AC) pavements in Nevada using the AASHTOWare® Pavement ME software. This research also explored the possible implementation of a hybrid approach for AC damage characterization to overcome the challenges associated with the use of the Witczak model for estimating the undamaged dynamic modulus master curve of the existing AC layer. Two rehabilitation field projects were used as part of this study. The experimental plan involved falling weight deflectometer (FWD) testing in the right wheelpath before rehabilitation, analysis of core samples, estimation of an equivalent undamaged dynamic modulus, and estimation of equivalent damaged dynamic modulus from FWD backcalculation. The proposed hybrid approach consisted of conducting laboratory dynamic modulus testing on the collected core samples and estimating an equivalent undamaged dynamic modulus at the same FWD testing temperature and loading frequency. The pre-overlay damage, characterized based on the approach in Pavement ME Design software (i.e., using a Witczak prediction model and backcalculated modulus), showed overly high values that did not match with the collected pre-overlay distress data on either of the rehabilitation projects. Based on the findings from this study, the hybrid approach was recommended for implementation by Nevada Department of Transportation (NDOT) when designing AC overlay over polymer-modified asphalt pavements in Nevada. Recommendations for user inputs were also provided for future consideration in Pavement ME Design software.

Reflective cracking relief interlayer for asphalt pavement rehabilitation: from development to demonstration

Reflective cracking is one of the major type of distresses associated with the use of asphalt concrete (AC) overlay for rehabilitating deteriorated asphalt pavements. This paper briefly describes the research efforts completed in Nevada to identify the best promising techniques to mitigate reflective cracking in AC overlays under Nevada’s climatic and materials’ conditions. The main outcome of the study was the development of a preliminary performance-based mix design specification for an experimental stress relief course (referred to as ESRC) to be placed between the AC overlay and the milled AC surface. Consequently, in summer of 2015, the Nevada Department of Transportation (NDOT) implemented the developed specification on a demonstration project on US 95 in southern Nevada. The project included test sections with three different strategies: (1) AC overlay on top of the ESRC mixture, (2) AC overlay on top of the NDOT fine-graded Type 3 mixture (SRC-T3), and (3) AC overlay without any stress relief layer. An extensive laboratory evaluation was conducted on all three mixtures using both laboratory-mixed laboratory-compacted and field-mixed laboratory-compacted mixtures. Core samples were also collected after construction and were evaluated for in-place thickness and air voids as well as resistance to reflective cracking. The data showed promising results for the ESRC mixture in terms of its resistance to fatigue and reflective cracking while maintaining an acceptable level of stability and resistance to rutting. A windshield survey conducted approximately 13 months after construction showed no distresses in any of the surveyed sections. In summary, the study showed a very good performance for the ESRC mixture thus far, making it a promising technique for reflective cracking mitigation in Nevada.

Earthquake Damage Estimations: ShakeCast Case Study on Nevada Bridges

This case study evaluates the vulnerability of Nevada bridges relative to earthquake hazard using two different methods. First, a distributed set of 112 realistic earthquake scenarios were processed with USGS program ShakeMap, and site-specific ground motion levels extracted for 1831 bridges in Nevada using ShakeCast. Second, using hazard curves underlying the 2014 USGS National Seismic Hazard Map (NSHM), return periods for earthquakes causing extensive damage to bridges were extracted and compared to the 1000-year design level adopted by the AASHTO. Lower capacities than those used in ShakeCast were proposed for five continuous bridge types based on a literature review. Scenarios provide points in a deterministic seismic hazard approach, with large earthquakes on known faults. NSHM hazard curves are based on a probabilistic approach. A graphical method is presented to unite the two approaches. A list of potentially vulnerable bridges was developed for Nevada Department of Transportation (NDOT) use in bridge retrofit planning. As a continuing benefit, ShakeCast now operates in Nevada to provide near-real-time inspection priorities in the event of a serious earthquake.

Predicting Crash Rate Using Logistic Quantile Regression With Bounded Outcomes

Various approaches and perspectives have been presented in safety analysis during the last decade, but when some continuous outcome variables take on values within a bounded interval, the conventional statistical methods may be inadequate, and frequency distributions of bounded outcomes cannot be used to handle it appropriately. Therefore, in this paper, a logistic quantile regression (QR) model is provided to fill this gap and deal with continuous bounded outcomes with crash rate prediction. The crash data set from 2003 to 2005 maintained by the Nevada Department of Transportation is employed to illustrate the performance of the proposed model. The results show that average travel speed, signal spacing, driveway density, and annual average daily traffic on each lane are significantly influencing factors on crash rate, and logistic QR is verified as an alternative method in predicting crash rate.

Highway Expenditures and Associated Customer Satisfaction: A Case Study

This study analyzes the satisfaction of the Nevadans with respect to their highway transportation system and the corresponding expenditures of Nevada Department of Transportation (NDOT). A survey questionnaire was designed to capture the opinions of the Nevadans (customers) about a number of characteristics of their transportation system. Data from the financial data warehouse of the NDOT was used to evaluate expenditures. Multinomial probit models were estimated to study the correlations between customers’ opinion and the government expenditures in transportation. The results indicate the customer satisfaction is decreasing with respect to traffic safety throughout Northwestern and Southern Nevada highways. In addition, users of Northwestern highways are more likely to be satisfied, compared to their counterparts, with increasing construction spending to reduce the time taken to complete construction projects. In Southern Nevada highways, customers’ satisfaction increases with the expenditures associated with reduction of congestion. These insights are examples of the conclusions that were obtained as a consequence of simultaneously considering customer satisfaction and the corresponding expenditures in transportation.

The Development of Regression Models to Estimate Routine Maintenance Costs for State Highway Infrastructure

Literature review indicates that most studies on pavement management have been on reconstruction and rehabilitation, but not on maintenance; this includes routine, corrective and preventive maintenance. This study developed linear regression models to estimate the total maintenance cost and component costs for labor, materials, equipment, and stockpile. The data used in the model development were extracted from the pavement and maintenance management systems of the Nevada Department of Transportation (NDOT). The life cycle maintenance strategies adopted by NDOT for five maintenance prioritization categories were used as the basis for developing the regression models of this study. These regression models are specified for each stage of life-cycle maintenance strategies. The models indicate that age, traffic flow, elevation, type of maintenance, maintenance schedule, life cycle stage, and the districts where maintenances are performed all are important factors that influence the magnitude of the costs. Because these models have embedded the road conditions into the life-cycle stage and type of maintenance performed, they can be easily integrated into existing pavement management systems for implementation.

Cost and Benefit Evaluation of Graffiti Countermeasures on the Nevada Highways

Nevada is one of the major states that are currently suffering from graffiti problem. It was estimated that graffiti costs Southern Nevada around $30 million per year. The major highway structures that were suffering from graffiti were bridges, sound walls, retaining walls and traffic signs. Removing graffiti from these infrastructures was a big challenge to the maintenance division of Nevada Department of Transportation (NDOT). Thus, the department was looking for cost effective proactive countermeasures to prevent graffiti on highway infrastructure. This study first identified a spectrum of proactive countermeasures, and then evaluated them by conducting a cost-benefit analysis. Pedestrian fencing and chain link fence were found to be cost effective countermeasures for preventing graffiti on bridges and sound walls. However, for relative long sound walls, the chain link becomes less cost effective. Rat guard was found to be cost effective for road signs; however, it was more useful for traffic signs that are located in the area where the taggers cannot find the way to bypass the rat guard. Coating and landscaping were found to be cost effective for small structures. The security camera countermeasure was not cost effective at the locations where the reduction in graffiti was small. The software for spectrometers was relatively high cost and might hinder the cost effectiveness of this countermeasure. To reduce the cost of the software, developing the software internally could be adopted. And finally, the electronic database was recommended since it was not difficult to develop and maintain.

MSE wall geogrid tensile strength at high temperature sites

The Nevada Department of Transportation is currently considering to use geosynthetic reinforcements for mechanically stabilised earth walls in Nevada. Geosynthetic reinforcement avoids corrosion and is often cheaper and easier to install during construction. However, specific to conditions in southern Nevada, geosynthetic materials may have other potential degradation issues, for example, uncertainty of long-term field performance at high temperatures. These temperatures may substantially degrade the tensile strength and creep of geosynthetic materials because their mechanical behaviour is temperature sensitive. This study focused on the tensile strength degradation of geogrid reinforcement, in which a simple scheme is proposed to obtain a more realistic strength reduction factor for design, that is, RF D, at high-temperature sites. The scheme combines the effects of the following important design factors: site-specific air temperature history, numerical thermal modelling to establish soil backfill temperatures and laboratory testing at high temperatures. It addresses the effects of both long-term exposure to high temperatures and load level on the design strength of geogrids. The proposed approach has been illustrated using temperature data for Las Vegas, NV, and is easily adaptable to any location and geosynthetic reinforcement.

Impact of lime on the mechanical and mechanistic performance of hot mixed asphalt mixtures

The purpose of this research was to evaluate the impact of hydrated lime on the mechanical and mechanistic performances of typical hot mixed asphalt (HMA) mixture. This research differed from previous studies in several respects. First, since lime is used in HMA primarily for anti-stripping benefits, previous studies rarely quantified lime's other performance benefits. Second, because testing is typically performed on only the HMA mixture being considered for a project, and only as necessary to satisfy specifications, typical studies do not capture the full range of failure modes and environmental stresses. Furthermore, once specifications are met, test results are rarely translated into pavement performance characteristics. This research, by contrast, evaluated two typical HMA mixtures from the northern part of Nevada and two HMA mixtures from the southern part of Nevada used by Nevada Department of Transportation with the most widely accepted laboratory tests. The Hveem mix design method was used for all eight mixtures. The mixtures were evaluated at the unconditioned (i.e. 0 freeze–thaw (F–T) cycles) and conditioned (i.e. 6 F–T cycles) stages. The moisture damage was evaluated through the dynamic modulus test at various temperatures and frequencies. The repeated load triaxial test was used to evaluate the permanent deformation of the mixtures. The flexural beam fatigue test was used to assess the fatigue resistance and the thermal stress restrained specimen test was conducted to evaluate thermal cracking resistance. This was followed by a comprehensive mechanistic analysis using the Pavement-ME design software, previously named MEPDG, in order to quantify the impact of lime on the long-term performance of asphalt pavements. Overall, the laboratory test results as well as the mechanistic analysis showed significant improvement in Nevada's mixtures performance when hydrated lime was utilised.

Forecasting of Financial Series for the Nevada Department of Transportation Using Deterministic and Stochastic Methodologies

In this research, a set of financial series was forecasted using data from the Nevada Department of Transportation (NDOT) with the objective of facilitating financial management and associated decision-making. Both deterministic and stochastic methods for seven financial time series, which were independent and univariate, from NDOT's financial data warehouse. Data from 2001 to 2014 were annually and equally spaced. The data series included drivers’ license fees, federal aid revenue, gas tax revenue, motor carrier fees, registration fees, special fuel tax revenue, and total state revenue. The deterministic forecasting methods used included Simple, Holt, Brown, and Damped Trend, and the stochastic forecast used ARIMA (p, d, q). The Simple and Holt methods provided an adequate forecast for 28% of the cases. Brown's method provided an adequate forecast for 44% of the cases. However, the stochastic process, the ARIMA method, did not find an acceptable goodness of fit. An absence of large datasets likely precluded an appropriate estimation when using the ARIMA (p, d, q) method. Tests were performed using functional curves including linear, logarithmic, inverse, quadratic, cubic, growth-exponential, and logistic. The best fits were obtained using the cubic functional form, with an average coefficient of determination of 82%.

General guidelines to highway agencies to enhance their local pavement rating systems: A case study of nevada’s pavement rating system

Evaluation of pavement condition is the principle source for the effective management of the pavements within any network or state. Many highway agencies within United State are using different pavement rating systems to evaluate their pavement condition. The data collection system, measurement units, calculation techniques have been modified and updated by several states with technological development with time. Recently, several highway agencies are willing to update their old pavement rating systems or gradually switch to more accurate rating systems but facing difficulties. This paper focuses on the potential enhancement on the Pavement Rating Index (PRI) used by Nevada Department of Transportation (NDOT) and thus eventually transitioning to the Pavement Condition Index (PCI) developed by U.S. Army Construction Engineering Research Laboratory. Pavement condition data that were utilized to calculate PRI over the last 15 years were converted into PCI compatible format using a suitable conversion technique. Estimated PCI values were plotted against its corresponding PRI showed moderate correlation with R² value of 0.57. The current PRI system was then enhanced to eliminate the observed deficiencies in the current system. The statistical relationship between the enhanced PRI against PCI showed improved correlation with R² value of 0.78. The study concluded that a successful switch from PRI system to PCI system can be achieved in Nevada while maintaining the use of the historical pavement condition data. This paper provides general recommendations for other agencies that are transitioning from local pavement rating system to PCI system.

Cold In-Place Recycling in Nevada

The Nevada Department of Transportation has long used CMS-2S emulsion for cold in-place recycling (CIR) projects and has recently introduced solvent-free (Reflex) emulsion and polymerized asphalt surface sealer (PASS) emulsion. An observed difference in CIR performance with changing emulsion technology prompted the assessment of long-term performance of CIR pavements throughout Nevada. The evaluated CIR projects were divided on the basis of rehabilitation type and then subdivided on the basis of emulsion technology. The study revealed that CIR followed by a hot-mix asphalt (HMA) overlay and a surface treatment performed much better on high-volume roads than did CIR with surface treatment on low-volume roads. Transverse and longitudinal cracking were the major types of distresses in CIR pavements. Approximately 50% of pavements constructed with HMA overlay and surface treatment and 95% of pavements constructed with only surface treatment experienced transverse cracking during service life. About 30% of pavements constructed with HMA overlay and surface treatment and 70% of pavements constructed with only surface treatment experienced longitudinal cracking. The CIR technology with HMA overlay and surface treatment significantly improved rutting resistance and pavement roughness. Climatic condition, CIR layer thickness, and surface treatment types were found not to affect performance of roads with CIR. The CMS-2S projects constructed with surface treatment and 1.5- to 2.5-in. HMA overlay were predicted to reach a pavement condition index value of 60 for rehabilitation in 15 years. The CMS-2S projects constructed with 3 to 4 in. of HMA overlay performed excellently up to 9 years and were expected to last more than 20 years before rehabilitation. The CIR with CMS-2S and PASS emulsions constructed with surface treatment were predicted to reach the index value of 60 after 15 and 19 years, respectively. However, Reflex emulsion was predicted to need rehabilitation after only 6 years.