Vehicles approaching a two-way, stop-controlled intersection from the minor roadway will wait for a large enough gap in the traffic on the major roadway before entering the intersection. The primary method for modeling intersections for both safety and operations is to determine a critical gap size such that a vehicle waiting at the stop sign will enter the intersection if the gap on the major roadway is larger than the critical gap. The method that is currently most accepted for measuring the critical gap is a maximum likelihood estimation developed by Troutbeck. The Troutbeck method may yield biased results and cannot be used with data sets that contain only rejected gaps. This paper proposes an alternative model for estimating the critical gap that is unbiased and can be used with naturalistic data. The proposed model requires that the gap distribution of the major street be known. This proposed model is compared with the Troutbeck model through a Monte-Carlo simulation. The proposed model yields accurate estimates of the mean critical gap as long as accurate estimates of the major street traffic are used.

This research is aimed at facilitating the understanding of the restrictions of convoy movement with object shapes as they might apply to ground vehicles maneuvering in a theater-of-operations. Such a theater would include civilian or military disaster evacuation/relief and military security or logistics operations. The goal of the overarching study was first to identify routes for maximal throughput rate that will facilitate the maneuver of a convoy unit omnidirectionally (radially) to different localities at different elapsed times. The focus of this study was to characterize several models for physical boundary conditions. Having done so, they would be used to evaluate the passability of convoy vehicles through streets in an urban environment under different conditions of road geometry, especially at an intersection. Special cases are also evaluated to study the capability of the general models. Models for radius and length of curvature are also developed for different traffic geometrics such as intersections, curvature, and a circular island in an intersection. In all modeling approaches, detailed descriptions of the derivations are illustrated with numerical examples and figures. These road geometrics will help estimate the reduction of traffic speed for deployment of ground vehicles.

The current wireless technological advancements in video surveillance are bound to shape the future of online traffic monitoring applications for intelligent transportation systems. The authors present the effect of using $802.11\mathrm{b}/\mathrm{g}$ wireless technology on real-time traffic surveillance systems. Although numerous studies have focused on studying the quality requirements for video streaming using a simulation environment, there is limited information on such performance in a real world environment. This study analyzed key video quality parameters, including packet jitter and packet rate, suggesting necessary guidelines for the transportation agency personnel to use when evaluating and selecting surveillance and communication tools. Study of the packet jitter showed that jitter and skipped video are strongly correlated with one another. Moreover, tolerated jitter ranges were identified that would ensure smooth traffic surveillance video. Findings indicated that to avoid jitter-related problems and to minimize the discontinuity of surveillance video, a 1-s play-out buffer size should be added to traffic surveillance communication systems. Analysis of packet rate suggested that an average value of $23\mathrm{packets}/\mathrm{s}$ can ensure smooth video continuity for traffic surveillance applications. Further analysis of multiple surveillance videos streaming simultaneously revealed the importance of knowing the available bandwidth for video transmission. Multiple video streaming over a wireless network indicated that the available bandwidth plays an important role in deciding the perceptual quality of the video.

Animal-vehicle collisions (AVCs) cause hundreds of human and wildlife animal fatalities and tens of thousands of human and wildlife animal injuries in North America. It is estimated that AVCs cause more than $1 billion in property damage each year in the United States. Further research efforts are needed to identify effective countermeasures against AVCs. Two types of data have been widely used in AVC-related research: collision reported (CRpt) data and carcass removal (CR) data. However, previous studies showed that these two data set are significantly different, implying the incompleteness in either set of the data. Hence, this study aims at developing an algorithm to combine these two types of data to improve the completeness of data for AVC studies. A fuzzy logic–based data mapping algorithm is proposed to identify matching data from the two data sets so that data are not overcounted when combining the two data sets. The membership functions of the fuzzy logic algorithm are determined by a survey of the Washington State Department of Transportation CR staff. As verified by expert judgment collected through another survey, the accuracy of this algorithm was approximately 90%. Applying this algorithm to the WSDOT data sets identified that approximately 25∼35% of the CRpt data records have matching pairs in the CR data. Compared with the original CR data set, the combined data set has 15∼22% more records. The proposed algorithm provides an effective means for merging the CRpt data and the CR data. Such a combined data set is more complete for wildlife safety studies and may provide additional insights into understanding the issue of AVCs.

Progression bandwidth maximization is one of the most important signal coordination strategies for urban arterial signal control. MAXBAND and MULTIBAND have implemented a weighting factor that is capable of adjusting the bandwidth according to unbalanced bandwidth demands in a two-way bandwidth maximization problem. The maximum bandwidth solution may not be achieved with certain values of weighting factors; therefore, users may need to have a well-developed idea about what weighting factor to use in order to not compromise the total bandwidth. In this paper, we propose a new two-way bandwidth maximization model that not only maximizes the total bandwidth, but also introduces a bandwidth proration impact factor. This impact factor allows the user to control the importance of satisfying the target bandwidth demand ratio. Numerical examples have demonstrated that the new model has the following advantages: (1) when two-way progression solution is not physically possible, the model first guarantees maximum total bandwidths and then automatically prorates the bandwidth fully to the direction with higher traffic demand; (2) when two-way progressions can be achieved, the model not only guarantees maximum total bandwidth but also automatically prorates the bandwidth in a ratio as close as possible to the ratio of bandwidth demands.

The authors present a procedure for allocating resources for implementing safety improvement alternatives at urban intersections over a multiyear planning horizon. The procedure, on the basis of optimization techniques, attempts to maximize benefits measured in dollars saved by reducing crashes of different severity categories subject to budgetary and other constraints. It is presented in two parts: (1) a base case including the objective function and a set of mandatory constraints; and (2) additional policy constraints/special features that can be separately incorporated to the base case. Demonstration of the procedure is presented on intersections in the Detroit metropolitan region, in which economic losses resulting from traffic crashes at intersections are estimated to exceed $4 billion annually. The proposed model can allocate resources for safety improvement alternatives over a planning horizon, given a number of independent locations and a number of mutually exclusive alternatives at each location. The policy constraints provide the analyst the flexibility of adding equity, urgency, and other features to the base case. An integer programming technique is applied to solve the demonstration problem.

Inferences on hurricane evacuation behavior are usually drawn through developing empirical models. These models are estimated using data that are specific to a given hurricane context. One important issue, therefore, is whether such models are applicable to different hurricane contexts. This paper investigates this transferability issue of evacuation choice models across different hurricanes. Initially, we estimate three separate models of the binary decision to evacuate or not, using data sets from three hurricanes (Andrew, Ivan, and Katrina) that occurred at different periods. Then a joint model is estimated combining these three evacuation data sources. When estimating the model jointly, the differences among the scale parameters of the data sets are specifically accounted for. The results from joint and separate models are then statistically tested to evaluate whether evacuation decision model parameters are transferable across different hurricane contexts. The result from the statistical test suggests that the parameters of the evacuation choice models are transferable over different hurricane contexts in similar regions, an important implication for policymakers and emergency preparedness agencies.

In the highway development process, the first planning stage is that of selecting a corridor along which the highway is to pass. Highway corridor selection represents a multicriteria decision process in which a variety of social, environmental, and economic factors must be evaluated and weighted for a large number of corridor alternatives. This paper proposes a demand-based approach to provide a set of potential corridors. The problem is formulated as a continuous location model that seeks a set of optimal corridors with respect to the demand of potential users while satisfying budget constraints. This model uses geographical information to estimate the length-dependent costs (such as pavement and construction cost) and the cost of earth movement. A procedure for finding the best local minima of the optimization model is proposed. This method is tested by using the Particle Swarm Optimization algorithm, two algorithms of the Simulated Annealing type, and the Simplex Nedelmar method. An application using the Castilla–La Mancha’s geographic database is presented.

The geometric design of highway elements is based on a set of standards that do not consider the risk levels associated with these designs. Safety elements including risk measures need to be identified and incorporated into the design process. The focus of this paper is a procedure that can be used by practitioners as a framework to conduct trade-off analyses between risk and service measures of specific design elements. The procedure builds on the randomness of parameters affecting the design attributes of any highway element. By accounting for the inherent variability of the determining parameters, random distributions of the design element can be derived. Then, using stochastic simulation, each of the design values can be tested to assess its risk measures. As a result, a risk index can then be attached to every design value in the random distribution. Finally, level of service (LOS) measures can be estimated and a trade-off analysis between LOS and safety could be conducted. The application focused on the design of the passing sight distance (PSD), which is an example of a highway element traditionally analyzed with no risk measures. Within the analysis, the risks and LOS measures associated with the use of the current PSD standards were assessed. The American Association of State Highways and Transportation Officials (AASHTO) Green Book values were shown to be conservative. The Manual on Uniform Traffic Control Devices (MUTCD) values fall within the acceptable risk and level of service (LOS) levels.

Left-turn gap acceptance at an unsignalized intersection is dependent on many factors. The Highway Capacity Manual (HCM) uses a single value of critical gap for all types of intersections; however, this may be oversimplistic and lead to inaccurate estimates of left-turn delay and capacity. Most existing studies also do not differentiate between gap and lag when evaluating gap acceptance. In this paper, binary logit models were developed to estimate the probability of accepting or rejecting a given gap or lag for a left-turning vehicle from a major road at an unsignalized intersection considering a number of potential influencing factors. Gap acceptance behavior was found to be influenced by the type of gap presented to the driver (gap or lag). Gap duration, total wait time, time to turn, distance to next signal downstream, and median type were found to be significant factors in predicting the probability of accepting or rejecting a gap. In the model for lag acceptance lag duration, time to turn, crossing width, speed limit, and distance to next signal downstream were found to be significant. Equations for estimating the critical gap and lag were developed. Critical gap and lag were found to be varying over a wide range of values depending on the type of intersection. The range was smaller for critical gaps than lags. The findings from this study can improve operational analysis of left turns at unsignalized intersections by using different critical gaps for different traffic and geometric conditions.

Modeling of the pavement image formation process by using reflection properties of macrotexture showed that digital images of concrete pavements can be used to monitor pavement wear. The specific optical characteristics of images and the optimum camera settings that can be used for this purpose were determined by theoretically formulating the Bidirectional Reflection Distribution Function (BRDF) of surface texture with uniform color. In the analytical phase of the study, desired levels of pavement texture were generated by combining a series of 3D sine surfaces of varying wavelengths and amplitudes. The optimum specular settings of the overhead point light source and the digital area-scan camera for effective highlighting of the imaged wheel path macrotexture were determined with an analytical formulation on the basis of a simplistic and physically meaningful BRDF model. It was also shown that the images obtained by the theoretical formulation closely resemble those captured from a similarly textured experimental surface under identical lighting and imaging conditions. In particular, the pavement image formation model revealed that quantifiable changes in the brightness of images do occur because of changes in texture depth and spacing (wavelength). In the next phase of the study, the traffic-induced pavement wearing process was simulated by gradual smoothening of the modeled surfaces, and then images corresponding to each wearing stage were generated. The theoretically predicted variation of the image brightness resulting from wear was experimentally verified by using images from a gradually worn-out concrete specimen. Finally, it was illustrated how the brightness evaluation of wheel path images has the potential to be a screening tool to monitor the degradation of macrotexture and, hence, the skid-resistance of pavements at the network-level.

Because pervious concrete pavement (PCP) has a porous structure and can percolate water to an underground layer, it has been proposed as a stormwater best management practice (BMP), an environmentally friendly product, and sustainable paving materials. This porosity makes PCP susceptible to freeze-thaw damage in cold climates. Therefore, PCP has not been widely applied and investigated in such a climate. Long-term performance data are rarely available, and no performance model has been developed for PCP to date. The main objective of this research is to integrate expert knowledge (using the Markov-chain process) and experimental data (PCP field investigations) to build a performance model for PCP through incorporation of the Bayesian technique. The combination of these sources of data is an efficient and effective approach to build a performance model for a new type of pavement, such as PCP, which has not had a long-term performance database. As a result, a robust linear performance model is developed and applied to predict the service life of PCP. The service life of PCP is estimated to be approximately nine years using the developed performance model. In general, the expert knowledge leads to more conservative results rather than experimental data.

An assessment and comparison of the effect of pavement macrotexture on crashes along Interstate corridors with tinned concrete and asphalt pavement is presented in this manuscript. Data obtained for I-40 in Durham County, North Carolina, with tinned concrete pavement, and I-40 in Pender County, North Carolina, with asphalt pavement were used for evaluation. Laser profilometer data obtained from the North Carolina Department of Transportation (NCDOT) were processed to calculate pavement macrotexture at 100-m ($\sim 330$ft) sections according to the ASTM standards. Crash data for each section was integrated with the calculated pavement macrotexture. Generalized linear models (GLM) were developed by considering predictor variables such as million vehicle miles of travel, the number of interchanges, the number of bridges, the number of culverts, and the number of grade-separated interchanges along with pavement macrotexture. The negative coefficient obtained for pavement macrotexture indicates that the number of crashes decreases as pavement macrotexture increases. The statistical significance of pavement macrotexture on a logarithm of crashes, when compared with other predictor variables, was observed to be stronger along the study’s corridors. The effect of pavement macrotexture on crashes was also observed to vary by the pavement type. Results obtained indicate that maintaining pavement macrotexture greater than or equal to 2.032 mm (0.080 in.) on tinned concrete pavements, and greater than or equal to 1.016 mm (0.040 in.) on asphalt pavements, would reduce crashes and enhance safety through improved braking performance on Interstates.

The purpose of this research effort was to develop a new performance prediction model for paint pavement markings that includes the effect of snow removal operations. The paper first develops a model based on data from North Carolina. The authors then apply the model to a small stretch of road in Ohio to explore the utility of the model in other states. Recently proposed Manual of Uniform Traffic Control Devices (MUTCD) minimum standards for pavement marking retroreflectivity were combined with the newly developed degradation model to determine the remaining service life of four road segments due for replacement according to standard operating procedure. This model showed 3 years of service life remaining for two of the road segments, indicating that replacement is unnecessary. Using the model developed in this paper, the remaining service life of a paint pavement marking can be estimated, and asset managers can avoid premature replacement of pavement markings. A key finding of this research is that each snow removal event subtracts more than 1 month of service life from paint pavement markings.

In this study, an attempt was made to evaluate and select an optimal Maintenance and Rehabilitation (M&R) strategy for a designed flexible pavement by integrating Life-Cycle Cost Analysis (LCCA) and California Mechanistic-Empirical (M-E) design procedures (CalME). A 20-year design life pavement stretching 11.27-km-long section of 4-lane Highway 53, in Lake County, California is considered for this project level study. Three M&R strategies available in the CalME program were evaluated including, Extended Pavement Preservation (EPP), Preservation-Preservation-Rehabilitation (PPR), and Rehabilitation only (R). These strategies are applied as certain levels of distresses (rutting and cracking) are reached. The California-customized RealCost LCCA program was also employed to compare the various M&R strategies using the Equivalent Uniform Annual Cost (EUAC). LCCA demonstrated that EPP was the best economical alternative to maintain the pavement in a good usable condition for as long as 80 years of service. The methodology employed in this paper also demonstrated that extended life pavement may be achieved from a 20-year design by selecting the optimal preservation techniques and optimizing their time of application.

Pervious concrete pavement (PCP) is of significant importance in the field of stormwater management in terms of reducing runoff volume. Stormwater managers should initially ensure that PCP adequately performs over time to be able to implement it in a stormwater management system. Performance models are intended to predict the performance of an asset over its service life. To develop a performance model commonly long-term performance data are essential. No performance model has been developed for PCP to date because PCP long-term performance data are rarely available. In such a case, expert knowledge is an alternative method to collect data for developing a performance model. This research aims to develop performance models for PCP for the first time by using an integrated Markov chain technique (combination of homogenous and non-homogenous techniques) through incorporation of expert knowledge. Both deterministic and stochastic approaches are applied to build up Markov models by using expected values and the Latin hypercube simulation technique, respectively. Both approaches provide consistent results although the stochastic Markov model provides more detailed results. Short-term experimental field data are also incorporated to validate the Markov performance models.

After decades of research and development, a fully automated system for pavement crack detection with an intensity-based two-dimensional (2D) imaging data acquisition system under different lighting and low intensity contrast conditions still remains a challenge. With the advances of sensor technology, a three-dimensional (3D) laser technology that can collect high-resolution 3D continuous transverse pavement profiles for detecting cracks on the basis of their 3D elevation rather than 2D intensity has become available. This study, sponsored by the U.S. Department of Transportation (US DOT) Research Innovative Technology Administration (RITA) program, evaluates the feasibility of using emerging 3D laser technology to detect cracks under different lighting and poor intensity contrast conditions. For this purpose, 3D surface data from laboratory tests on cracks ranging from 1 to 5mm wide and tests on the actual pavement cracks of different widths and depths and under different lighting conditions were performed. The dynamic-optimization-based crack segmentation method was employed to detect cracks. A linear-buffered Hausdorff scoring method was used to quantitatively evaluate the crack segmentation performance by comparing the detected cracks with the manually established ground truth. The preliminary test results show that: (1) the 3D laser system can effectively detect cracks equal to and greater than 2 mm wide under controlled laboratory environment, (2) it can achieve consistent results when detecting cracks under different lighting conditions (i.e., nighttime, daytime with shadow, and daytime no shadow), and (3) it can detect cracks with low intensity contrast. Future research is recommended.

This paper addresses the problem of uncertainty management for the Mechanistic-Empirical Pavement Design Guide (MEPDG). Specifically, development of an all-inclusive approach to uncertainty management in which model uncertainty and input parameter variability are taken into consideration is presented in this paper. A Gaussian process surrogate model is chosen in this paper as a potential model for the MEPDG design software, and model verification metrics are included to assess the ability of the surrogate model to predict MEPDG output. The construction of a surrogate model that emulates the MEPDG will reduce the computational expense for uncertainty analysis but will introduce another source of uncertainty. Uncertainty propagation of these major sources of uncertainty is performed for a case study. The relative effects of these three major sources of uncertainty are investigated, and the influences of these sources of uncertainty are discussed utilizing the results from the uncertainty propagation. Reliability analysis incorporates the proposed methodology to investigate the effect of these sources of uncertainty for a typical flexible pavement design.

Flushing is a pavement surface defect that affects the structural integrity of thin-sprayed seal (chip seal) surfacings. Analysis was carried out on pavement performance data to determine the combination of factors that provides the best indication of flushing occurrence on in-service pavements. Data were sourced from the Long-Term Pavement Performance (LTPP) programme in New Zealand as well as from field testing. The LTPP data were analysed in four categories; pavement composition characteristics: traffic-related factors, climatic factors, and effects of other pavement defects. Factor and correlation analyses were used to determine and investigate the factors that showed significant relationships to flushing. Surface thickness, surface age, surfacing type, and rutting were found to have statistically significant correlations to flushing. Field testing provided data relating to the soil moisture environment under the pavement. The dry density and water content of soil were identified as having significant correlations to flushing. Regression analysis of the combination of these factors yielded a robust model to identify flushing.

This paper presents an algorithm to predict one-dimensional (1D) temperature profiles in a multilayered pavement system on the basis of measured surface temperature data. The model inputs are pavement layer thicknesses, thermal conductivity and diffusivity of layer materials, average initial pavement temperatures along pavement depths, and measured pavement surface temperature data. The main mathematical tools employed in deriving the analytical solution of pavement layer temperature predictions are the Laplace transform and numerical inverse Laplace transform. Measured in situ temperature data from a two-layer flexible pavement system demonstrate that the derived analytical solution generates reasonable temperature profiles in the asphalt concrete layer. The main advantages of the proposed algorithm are that it can rapidly predict the pavement temperature profile when the thermal conductivity and diffusivity values of the layer material are selected and the surface temperature data are measured at end points of each equally spaced time interval. Climatic data, such as air temperature, solar radiation intensity, and wind speed, are not needed to implement this algorithm. This algorithm can be applied to assist field engineers in estimating temperature profiles in a multilayered pavement system for the period during which falling weight deflectometer (FWD) tests are performed.