An analytical framework and procedure is proposed in this paper to incorporate pavement skid resistance requirements in asphalt mix design, as part of the overall asphalt pavement design process. The concept is introduced with the aim to overcome the inadequacy of current pavement design procedures, asphalt mix design in particular, in addressing pavement-related highway functional safety requirements. Central to the concept is the use of a theoretically derived finite-element simulation model to generate the skid resistance performance curve (i.e., skid resistance–speed relationship for a given water film thickness) of a pavement surface mix design, based on the input of two skid resistance values measured at different test speeds. Three highway functional safety requirements are addressed, namely the minimum safe terminal skid resistance, the maximum braking distance allowed, and the minimum hydroplaning speed. The proposed framework comprises three main components: (1) a laboratory-accelerated wear and polishing testing of a trial asphalt mix design; (2) estimation of in-service pavement skid resistance from laboratory friction measurements in the component from Step 1; and (3) an analytical simulation component that uses the finite-element model to derive the skid resistance and hydroplaning performance of the mix design, and checks for compliance with the three functional safety requirements. A numerical example is presented to demonstrate the steps involved and data required in the application of the proposed procedure. It is believed that the work presented offers a useful step forward toward bridging the gap between pavement design and functional requirements of highways.

A bonded concrete overlay of asphalt (BCOA), also known as whitetopping, is a thin concrete overlay placed upon a distressed asphalt pavement. The asphalt-resilient modulus is kept constant in current BCOA design procedures. This practice results in an underestimation of the damage as compared to when the hourly temperature variation of the asphalt is considered. The framework to establish an equivalent asphalt modulus involves generating a database of hourly middepth asphalt temperatures. This database should include hourly temperatures for different BCOA structures and a large range of geographical locations representing different climatic conditions. The hourly middepth asphalt temperatures are then used to generate hourly asphalt moduli using master curves. Through fatigue equivalency, the equivalent asphalt moduli are calculated for each month. In order to establish the relationship between the asphalt modulus and middepth temperature, the United States was divided into seven different zones according to their annual mean ambient temperatures. For each zone, models for predicting adjustment factors were developed for the asphalt modulus. Designers can calculate the monthly asphalt stiffness over the design life using the adjustment factor and reference month stiffness regression models. This asphalt stiffness is then corrected for aging and fatigue using the models incorporated into the AASHTO Pavement ME program. The methodology presented here has been incorporated into the recently developed BCOA mechanistic-empirical design and analysis procedure.

The interface damage as one of the most critical damage issues in railway slab tracks is evaluated in this work on the basis of reliability techniques and vehicle-track interactions. First, a coupled dynamics model of a vehicle and the slab track is developed involving nonlinear spring-damper elements for simulation of the interface damage. Furthermore, considering the random nature of the damage length, the damage height, the rail pad stiffness, and the elastic modulus of cement asphalt (CA) mortar layer, explicit mathematical expressions between the input stochastic variables and output dynamic responses are obtained on the basis of the combination of the response surface method (RSM) and the dynamic simulations of vehicle-track system. Subsequently, Monte Carlo (MC) simulations are performed for the probability analysis by directly using the response surface functions. Finally, by adopting the amplification factor (AF) of the dynamic response as the control indices, the damage assessment criterion and the corresponding safety threshold are suggested on the basis of the concept of reliability for the long-term dynamic performance of slab tracks. The results show that the interface damage has a significant influence on the slab displacement, the slab acceleration, and the dynamic stress of CA mortar layer; the damage length is the primary control index for the interface damage with a complete failure along the width of the slab track; the interface damage can be evaluated as damage levels I, II, and III when the survival probabilities for the AF of exceeding a certain value are 50, 30, and 10%, respectively; the safety thresholds for the interface damage levels I, II, and III are suggested to be 0.60, 0.85, and 1.05 m, respectively.

The January 2011 flood in Queensland caused severe damage to road infrastructures, which presented new challenges for the efficient management of the roads. To date, no deterioration model can accurately predict the impact of floods on pavements. To understand the impact of the January 2011 flood on the structural performance of flood-affected pavements, falling weight deflectometer (FWD) deflection data on flood-affected roads managed by the Brisbane City Council (BCC) and Roads and Maritime Services, New South Wales (RMS, NSW), Australia, were collected and examined. This paper proposes a deterministic model that expresses structural strength of pavements as a function of time. The model predicts the short-term behavior of a flexible pavement immediately after flooding. A comparison of before- and after-flood data, and flooded and nonflooded sections of the same road, indicates a consistent trend of decrease in strength due to its sustained submergence under flood water. The literature review indicates that structural strength deterioration was also observed for the pavements in New Orleans and Louisiana following Hurricanes Katrina and Rita in 2005. However, a trend of strength gain and even, in some cases, strength loss was also observed in the BCC data, which were collected 2 and 4 years postflood. The flood-affected pavements lost their structural strength faster than the predicted deterioration rate for which the road was designed. Importantly, the proposed model would facilitate the pavement engineers to quantify the postflood rapid deterioration of the structural strength. The model is sufficiently robust and can be adapted to other regions by calibrating for the local condition.

When designing median openings at divided highway intersections, it is important to consider the impacts of simultaneous (noncrossing) left turning movements by vehicles from opposing directions. The AASHTO Green Book recommends minimum lengths of median opening for different design vehicles and median widths. These minimum lengths are calculated based on assumed control radii for left turns from the divided highway into the crossroad and vice versa, and do not account for accommodation of simultaneous left turns. The Green Book minimum median opening lengths can prevent the capability for simultaneous left turns under certain circumstances. This study uses simulated vehicle turning paths to define the minimum conditions for accommodating simultaneous left turns and proposes corresponding revisions to the Green Book guidelines. The new method consists of determining the required control radius as a function of median width and calculating the minimum length of median opening by equations based on geometric relationships. The paper also describes the limitation of the Green Book methodology in addressing median openings with left-turn lanes, which is resolved by application of the proposed method.

Oversize-overweight (OSOW) permit programs allow carriers to move large, heavy, and often high-value freight on state and federal highways. This study analyzed six years of Wisconsin single-trip overweight permits and two years of Iowa single-trip overweight permits to visualize routing trends, identify heavily travelled highway segments, and provide support for mechanistic-empirical pavement design guide (MEPDG) analyses and pavement reliability research. The methodology used custom visual basic for applications (VBA) scripts for text parsing and route processing with results linked to a geographic information system (GIS) database. The results allowed for visualization of permit traffic, geospatial queries of permit routes, origin-destination analyses, and identification of heavily-used permit vehicle corridors. These results have numerous applications for highway design, bridge engineering, freight trend analysis, and highway system planning. Additionally, the methodology supports the generation of site-specific permit truck axle load spectra for integration into AASHTOWare MEPDG software traffic inputs. This methodology can improve the estimation of pavement damage from overweight permit vehicles, and results can inform OSOW program policies and assist in optimizing the permit issuance process.

The booming demand for rail services presents a challenge to railway capacity worldwide. Rail infrastructure managers are facing critical issues regarding how to efficiently utilize track resources and possibly optimize the allocation of track capacity. The traditional definition of rail capacity is usually based on the maximum number of trains that can be operated in a section of track in a given period. The unit ($\mathrm{trains}/\mathrm{h}$ or $\mathrm{trains}/\mathrm{day}$) does not reflect the train types or consider the revenue generated by each train. To overcome these limitations, this research proposed a new concept, profit-maximizing capacity (PMC), and established corresponding framework and models to maximize the profit generated from capacity according to demand and system characteristics. Computational results from the case studies demonstrate that the optimal usage of the rail infrastructure can be obtained through the use of PMC framework and models. Compared to the conventional capacity management strategy, the developed method can provide substantial benefit from more efficient track utilization and capacity allocation. Using this framework can help infrastructure managers formulate better capacity management strategies, thereby leading to a more efficient and sustainable railway system.

The directional distribution, also known as the D factor, is an important traffic parameter that is frequently used for design and operational performance analysis. This research analyzes the variability of the D factor for bicycle traffic and identifies the factors that lead to such variability. The importance of the D factor stems from its potential application in estimating the daily volume of one travel direction at a particular count station using the daily count of the other direction. This case takes place when the sensor installed on one direction is down because of malfunction. This research explores the temporal and spatial transferability of the D factors of bicycle traffic. Different sets of bicycle D factors were developed according to different criteria, and were further used for estimation purposes. The study made use of daily bicycle volume data, which were collected at 10 bidirectional count stations in the City of Vancouver, Canada, between 2009 and 2011. The results showed that the spatial transferability of the D factors led to an average estimation error of the opposite-direction daily bicycle volume of 18.3–20.0% for various sets of the D factor. The use of the best set of D factors along with daily and monthly adjustment factors for the estimation of the annual average daily bicycle (AADB) volume led to an average estimation error of 27.5%. Moreover, the estimation of the peak hour bicycle volume (PHBV) of the missing count was explored by applying the D factor and the design hour factor (known as the K-factor) sequentially and the estimation error was found to be approximately 27.3%. In the temporal transferability analysis, the D factors were developed and applied using data of the same count locations but on other days. The average estimation errors dropped significantly to approximately 11% for daily volume estimation, and 22% and 20.6% for the estimation of AADB and PHBV, respectively.