Development of an adequate performance model based on an appropriate condition index has been a major challenge for engineers particularly in case of a new type of design such as pervious concrete pavement structures (PCPSs) which suffer from limited long term performance data sets especially in colder climates. Soft computing techniques are significantly efficient at dealing with subjective, incomplete, and limited data. This paper proposes three most effective soft computing methods: fuzzy sets, the Latin Hypercube Simulation technique, and the Markov Chain process. A novel comprehensive condition index based on severity, density, and weighting factors of distresses occurring on PCPS has been developed incorporating fuzzy sets. A combination of homogeneous and nonhomogeneous Markov Chain has been applied to develop performance models. Transition probability matrices are presented using probability distribution functions rather than single values. A simulation technique is then used to incorporate the probability distribution function operations to compute the future condition of the pavements. The future performance of the pavements is expressed by both single expected values and suitable probability distribution functions. Ultimately, a probabilistic versus deterministic performance curve is presented.

The paper presents a method for estimation of power spectral density (PSD) parameters (unevenness index and waviness) of a longitudinal road profile in the short wavelength band from data collected by straightedge (SE) measurement (distance of contact points of the lath and maximum clearance from the straightedge between the supports). This method is based on the estimation of mean values of straightedge measurement parameters established by simulated artificial profiles of different waviness levels from 1.5 to 3.5. The method was validated on a series of simulated profiles with different waviness values and on some in-service road profile records. The method provides a reliable estimate of waviness as a complement to the currently used straightedge indicators based on the mean maximum clearance under the straightedge. Thus, mutual conversion between SE- and PSD-unevenness indicators is possible.

In a jointed concrete pavement, the dowel bar system and the aggregate interlock are two mechanisms for transferring wheel loads from one panel to the adjacent panel. The aggregate interlocking load transfer mechanism is effective for narrow joints while the dowel bar system works well for both narrow and wider joints. This paper examines the effects of different parameters on load transfer efficiency of a joint with the help of a three-dimensional finite-element model for the analysis of a dowel-jointed concrete pavement. The model was compared using experimental data available in the literature. The group action of the dowel bar system was also examined and useful relationships have been developed for estimation of the relative load shared by the individual dowel bars. These relationships will be useful in the design and evaluation of dowel jointed concrete pavements.

Data envelopment analysis (DEA) is a mathematical method based on production theory and the principles of linear programming. It enables one to assess how efficiently a firm, organization, agency, or such other unit uses the resources available (inputs) to generate a set of outputs relative to other units in the data set. Recent papers by different writers present different applications of DEA in the transportation engineering domain. All of these papers are published in transportation journals. These papers are mainly aimed at addressing the transportation-related issues and thus do not focus too much on the DEA concept itself. It can be asserted that DEA is very likely to be used more and more in the transportation engineering domain. Given this, there is a need for the transportation professionals to fully understand the DEA concept. It is essential for such a community to identify cases where the application of this innovative and powerful method can be useful to help the decision-making process, to accurately apply DEA in a particular setting, to derive meaningful conclusions from the obtained results, and to acknowledge the limitations of DEA in certain cases so as to approach the results with caution. The purpose of this paper is to illustrate to the civil engineering, more specifically to the transportation engineering community the use of this powerful approach in performing comparative performance measurement. Within this context, this paper will address a transportation-related problem by using the DEA approach. Different from the other papers containing transportation-related DEA applications (as mentioned above), this paper will discuss, in detail, the steps that need to be taken to generate the DEA model and solve it.

Porous pavements are asphalt or concrete pavement surfaces designed to allow moisture to flow through the surface into an underlying reservoir or into the subgrade soil. Porous pavements prevent pollutants from entering into the water table and therefore, are considered sustainable construction. However, porous pavements eventually fill with debris and get clogged, preventing water infiltration. Thus, the greatest barrier to the use of porous pavements is susceptibility to clogging. Therefore, a major maintenance objective for porous pavements is to prevent clogging of the void spaces within the pavement. This paper describes a potential process of removing particles trapped in the pores of the pavement by flushing water from the bottom to the top of the pavement. Four variables were evaluated in this laboratory experiment to determine effects on particle removal. These were: (1) water pressure; (2) clogging material; (3) pavement porosity; and (4) number of flushes. Results indicate the reverse flush process was effective on both types of clogging material evaluated, was independent of the pavement porosity, and worked for the lowest pressure tested.

This paper investigates the relationship between mode of asphalt mixture compaction and resulting mechanical performance in terms of stiffness modulus, permanent deformation and fatigue resistance. Four modes, comprising three laboratory methods of gyratory, vibratory, and roller compaction together with site compaction were included in the study. An interlaboratory program was undertaken using these compaction methods and three asphalt mixture designs. The results showed that mold based compaction methods, such as gyratory and vibratory, generally produce stiffer specimens with higher resistance to permanent deformation when compared to roller compacted or field specimens of comparable air voids. However, the results also showed significant variability within a particular compaction method between different laboratories. The statistical two-sample $t$ -confidence test was used to compare the sample means of air voids content and stiffness modulus between the different compaction methods. The statistical analysis showed that producing volumetrically identical asphalt mixture specimens using different compaction methods does not produce materials with identical mechanical properties. Statistical analysis was also undertaken on stiffness and permanent deformation results to provide engineers with the number of tests required to obtain a mean value within a certain accuracy of the “true” value, for a given confidence level. Stiffness modulus was found to have a far higher repeatability than permanent strain with the mode of compaction not affecting the variability of the results.

Moisture damage is one of the major problems that can be faced by a pavement during its design life. It can tremendously reduce a pavement’s strength and consequently its life. The test predominately specified to evaluate the moisture sensitivity of an asphalt concrete mixture is the modified Lottman test, currently specified as AASHTO T283. The problem with this test is that it assists in minimizing the problem, but it does not provide an accurate estimate of the anticipated moisture damage and in some cases it provides false results. The methodology used in this paper utilizes mixture dynamic modulus test methods, which are complimentary to the mechanistic-empirical pavement design guide (M-E PDG), in evaluating moisture damage in asphalt concrete pavements. Dynamic modulus tests are performed on both moisture conditioned and unconditioned samples and used as input parameters in the M-E PDG for estimating pavement performance. The methodology was applied on two projects and the results were compared to the results achieved using the AASHTO T283 methodology and dynamic modulus test results. The dynamic modulus test results show consistency with AASHTO T283 in identifying moisture sensitivity of a mixture. This paper outlines a method for evaluating hot mix asphalt moisture susceptibility using dynamic modulus testing and is compatible with the proposed performance testing for accompanying Superpave volumetric mix design. The results of the proposed mixture dynamic modulus moisture susceptibility method can also be used in the new M-E PDG for evaluating the moisture susceptibility effects of the tested mixtures. This in part allows for the evaluation of this environmental effect in the M-E PDG.

The Kansas Department of Transportation does routine roadwork that requires traffic on two-lane highways to be narrowed to one lane. This operation usually involves use of a pilot car to direct the flow of traffic. The main objective of this research was to determine the most cost-effective method of informing drivers of delay time when approaching a pilot car operation at the two-lane rural highway work zones. Since most rural construction zones are outside existing commercially available communication systems, such as cellular coverage, success of the project hinges primarily on the acquisition of a low-cost, easily deployable work zone data communication system. The method employed in the design of the notification system involved using global positioning system receivers to track the pilot car, an algorithm to determine the time the pilot car would take to reach the two ends of the work zone and 900-Mhz radio transceivers to send the information to the display. The information was displayed on a light-emitting diode timer, mounted on a specially designed sign. The system worked as designed during a 2-hour test run at an actual work zone and was well accepted by the drivers that were surveyed.

This paper investigates the quantitative characteristics of the vehicle arrival pattern on highways. Inspired from a remarkable finding on data network traffic that most data packet arrival patterns follow the self-similar process as opposed to the classical Poisson process, this paper aims to explore whether the vehicle arrival pattern on highways exhibit the self-similarity property and the corresponding time headway distribution it obeys. By using real highway traffic data provided by the Texas Department of Transportation, United States, this paper examines the existence of self-similarity characteristics on these vehicle arrival data. This is done by estimating the Hurst parameter, which is an index for self-similarity testing. Hypothesis testing for the Hurst parameter estimation shows that the highway vehicle arrival pattern under moderate to heavy traffic conditions exhibit the self-similarity behavior. Then, using the headway data recorded from the Federal Highway situated in Kuala Lumpur of Malaysia, this paper further demonstrates that the time headway of vehicles on the highways follows the heavy-tailed distribution rather than the classical exponential distribution. These two novel findings not only shed some light on the existence of a new distribution to describe the vehicle arrival pattern but also enrich the studies on traffic flow theory.

A method to determine the intensity of traffic is a key issue for the control of air pollution from urban transport in order to meet air quality requirements. In this study, by combining the definitions of environmental capacity and traffic capacity, the concepts of traffic-related environmental capacity and environmental traffic capacity are discussed. A mesh analysis method for environmental traffic capacity in urban areas has been developed by integrating the spatial segmentation method applied for the analysis of urban traffic system with the environmental spatial segmentation method. To calculate the spatial transfer coefficients of air pollutants between grids, a method of backing virtual point sources was established and applied to this case. The linear optimization model of traffic-related environmental capacity was established on a basis of the diffusion and transmission theories for air pollutants. Taking peak hours as an analytical period, we have established an urban environmental traffic capacity analysis model aimed at controlling various air pollutants emitted by vehicles. A case study shows that the model can analyze and calculate vehicle traffic volumes, which satisfy air quality requirements within specified temporal and spatial ranges.

Location selection problems have become one of most popular and important issues in the transportation and logistics systems. The purpose of this paper is to propose an integrated short-term and long-term multiple-criteria decision-making (MCDM) model for solving location selection problems. The advantages of the proposed integrated short-term and long-term MCDM model in this paper are not only to evaluate the short-term investment environment, but also consider the long-term operation environment. Many location selection methods have been proposed in the past, most of these methods were short-term evaluation approaches. Few studies proposed long-term evaluation methods for solving location selection problems. Short-term evaluation methods cannot be used to solve all manners of location selection problems. Sometimes, it is more realistic to deal with some specific location selection problems in the real world by using long-term evaluation methods. Thus this article attempts to fill this gap in current literature by proposing an integrated short-term and long-term MCDM model for solving location selection problems. Finally, the utilization of the proposed MCDM model is demonstrated with two case studies. In the first case study, a short-term transshipment location selection problem is shown. A long-term international distribution center location selection problem is introduced in the second case study. Furthermore, this paper presents a sensitive analysis of some examples of the problem while there is such integration. It highlights the importance of integrating the short and long-term evaluation method. The results show that the integrated short-term and long-term MCDM model in this paper can be used to explain the decision-making procedures for location evaluation and selection well.

This paper studies traffic features in a mixed traffic flow composed of motorized vehicles and nonmotorized vehicles near a bus stop within a completely different framework. Our work has taken the nonlane based behaviors of nonmotorized vehicles into account, which has seldom been considered in previous works. We have investigated flow rates as well as passenger transport capacity of the system. The traffic state diagram and the spatiotemporal pattern are presented as the inflow rates of motorized vehicles and nonmotorized vehicles change. A nonmonotonic change of passenger transport capacity is also identified at specific parameters. The influence of parameters such as stopped time of buses is discussed. These results are expected to shed some light on the management and design of urban mixed traffic systems.

Approximately one-third of the Saskatchewan provincial highway system is comprised of granular base structures with a thin asphaltic or double seal surfacing. Unfortunately, significant portions of the Saskatchewan thin granular system were not constructed to primary legal weight limit standards and are now exhibiting varying degrees load related distresses and in many cases, structural failures. Based on field performance observations, many of the failures are commonly observed within the granular base layer, particularly when the base is comprised of high fines content, and/or when exposed to high deviatoric stress states. A recent increase in load spectra due to increasing truck traffic has resulted in much of the Saskatchewan granular base systems needing structural rehabilitation. In order to optimize the road structure upgrade treatment, it is desirable to better understand the material constitutive relations of granular base materials across fines content, triaxial stress states, and load frequencies representative of those induced within thin granular base pavements in the field. This research employed triaxial frequency sweep characterization to characterize the mechanical material constitutive behavior of a typical Saskatchewan Type 33 granular base across increasing fines content, triaxial stress state, and load frequency. Based on the findings of this study, increased fines content was found to significantly degrade the mechanical behavior of the standard Saskatchewan Type 33 granular base material in terms of dynamic modulus and phase angle. This research showed that under realistic field state conditions in Saskatchewan, phase angle may be an indicator of elevated viscous behavior within the granular base. Based on the mechanical material properties measured, it was also found that the current specified limits for fines content may not be sufficient to ensure optimal mechanistic structural behavior of thin granular pavement systems under severe traffic load conditions.