Transportation agencies have suffered stringent funding shortages for the past several years. As a result, many pavement preservation and rehabilitation projects have been substantially delayed. The financial consequences of delaying pavement rehabilitation need to be quantified so funding needs can be justified scientifically. Although studies on the basis of hypothetical data have been conducted to evaluate the effect of delaying treatments, there is no research using actual data to quantify the financial consequences of delaying pavement rehabilitation. This study is motivated by the need to remedy this situation. A method that quantifies the financial consequences of delaying rehabilitation using real-world data is proposed. The proposed method uses life-cycle-cost analysis (LCCA) and a composite performance indicator, pavement condition rating (PCR), to determine the treatment timing. The proposed method is validated using actual pavement performance data and maintenance history from the long-term pavement performance (LTPP) specific pavement studies-5 (SPS-5) in California. These pavement sections have the same pavement structure, traffic volume, environmental features, and similar rehabilitation treatments, but they have different treatment timings. Their annual life-cycle costs are computed and compared to quantitatively evaluate the financial consequences of delaying treatment. Preliminary results show that delaying rehabilitation of pavement sections (prerehabilitation $\mathrm{\text{PCR}}\mathrm{\text{value}}<60$) increases the equivalent uniform annualized cost (EUAC) by approximately 27.7% for a 2-in. overlay and 28.3% for a 5-in. overlay compared with the timely rehabilitation of pavement sections. Future research is also discussed in this paper.

Accurate determination of critical structure responses plays a vital role in the ability of the Mechanistic-Empirical Pavement Design Guide (MEPDG) to achieve a reliable pavement design. In the MEPDG, the responses generated by a single axle are evaluated at a series of predefined locations, and responses under multiple axle gears are determined using the responses from a single axle following the principle of superposition. This research indicates that the approach currently employed in the MEPDG is able to identify the critical location and obtain the critical response for a tandem axle, while it is inadequate for a tridem or quad axle. The primary reason for the inadequacy is that the response along the outside axle of a tridem or quad gear is not computed and compared to responses at other locations. The erroneous critical location identified by the MEPDG for a tridem or quad axle will lead to an underestimated critical response and consequently an overpredicted pavement life. The results show that the fatigue lives of asphalt concrete (AC) and cement stabilized mixture (CSM) layers could be overpredicted by up to 50 and 200%, respectively. A new set of analysis locations are recommend in this study, and equations for computing responses under multiple axle gears using the principle of superposition are proposed for accurate determination of critical responses and prediction of pavement performance.

The objective of the study in this paper was to investigate the influence of warm mix additives on polymer-modified asphalt (PMA) mixtures in regards to engineering properties. Twelve PMA mixtures (four control PMA mixtures and eight warm PMA mixtures) were prepared by using two additives (Aspha-min and Sasobit), two binder sources, and two aggregate sources. An evaluation of all PMA mixtures included the following testing procedures: tensile strength ratio (TSR), asphalt pavement analyzer (APA), resilient modulus, and indirect tensile strength (ITS) after longterm oven aging. The results from this research generally indicated that (1) the PMA mixtures containing the additives can satisfy the current Superpave mixture requirements (including moisture susceptibility and rutting resistance) and (2) no statistical differences existed between the control and the warm PMA mixtures for the properties that the authors evaluated in this study, suggesting using of WMA technologies in PMA mixes has no negative effect on the mixture’s engineering properties.

Tests were conducted in the laboratory and field to determine the extent to which fluidized bed combustion (FBC) spent bed and pulverized coal combustion (PCC) fly ash, by products of the coal industry, can be used in low-volume county and secondary roads. Various proportions of prehydrated FBC spent bed (as a secondary aggregate and an agent to activate pozzolan oxides), PCC fly ash (as a primary cementitious binder), natural fine aggregate (as a primary filler), and a low dosage of Portland cement (as a secondary cementitious compound) were blended and compacted at their optimum moisture content to ascertain their suitability as base course materials. These tests and experiments were used to assess the performance of the selected PCC/FBC base course composites. On the basis of the results, thickness-design tables of PCC/FBC base courses were developed. Results indicate that the engineering properties of the PCC/FBC composites exceed those of the conventional mixes used in low-volume roads. The field results verified that the engineering characteristics of the laboratory mixtures can be easily duplicated in field.

For several decades, efforts have been made by engineers and researchers in road and airfield pavements and railroads to develop methods/procedures for accurate quantification of aggregate shape and packing properties. The difficult part of the process has been the fact that aggregate particles have irregular and nonideal shapes. New research capabilities, including laser-based technology, can effectively address the difficulties associated with aggregate shape measurements to optimize asphalt mix design. This paper introduces the use of a three-dimensional (3D) laser scanning method to directly measure the surface area of aggregates used in road pavements in South Africa. As an application of the laser-based measurements, the asphalt film thicknesses of five typical South African mixtures were calculated and compared with the film thicknesses calculated from traditional methods. Based on the laser scanning method, new surface area factors were developed for coarse aggregates used in the asphalt mixtures. Overall, the study demonstrated applicability of 3D laser scanning method to characterize coarse aggregates.

Traffic flows around roundabouts have been found to be dependent on origin-destination flows, but the true nature of this relationship is not properly understood. Present analyses are based on either gap acceptance models or empirical models. These models do not properly account for the impact of origin-destination flows on roundabout operations. This has limited the possibility to develop strategies that improve roundabout operations by controlling inflows. This research proposes a theory to analyze roundabout traffic flows and a strategy to determine inflows into a roundabout that would maximize the outflow from the roundabout. This strategy could be implemented through use of signals to meter vehicles at the entry. To achieve this, a theoretical framework is proposed based on the macroscopic fundamental diagram for urban networks. The theory and strategy is then tested using microscopic simulation. It was found that the outflow from a roundabout is dependent on the average flow and the average trip length around the roundabout. The average trip length is a function of the origin-destination flows.

This study uses the two-fluid model for traffic flow, to examine driver behavior during both wet and dry pavement conditions and various times of the day. It was found that parameters in the two-fluid model known to be strongly affected by driver behavior (particularly driver aggressiveness) were statistically different between wet pavement and dry pavement conditions. The results confirmed that drivers tend to behave more conservatively when the pavement was wet compared with dry. The parameters of the two-fluid model were found to be statistically different for the morning peak period from the midday and evening peak periods, the results of which indicated that drivers behave more aggressively during the morning peak. Although these findings have been observed in previous studies, they have not been quantified using traffic data. This study shows that the two-fluid model apart from being a measure of network performance may be able to unveil more about driver behavior. There is a strong possibility that the parameters of the model may be used by researchers as a surrogate measure of safety and could lead to a measure to evaluate aggressive driving.

This paper describes a study whose primary purpose is to better understand the relationship between freeway traffic flow and speed. Incidents of recurrent and nonrecurrent congestion were encountered at six radar collection northbound locations on New Hampshire interstate I-93 in July 2010. The root cause for the onset of the recurrent congestion is explained with exploratory data analyses and a time series modeling approach. A complex combination of present and past values of traffic flow, speed, and congestion state, a congestion history of lingering effect variables, can explain the triggering and mitigation of congestion events for a highly volatile traffic environment. The approach includes two mathematical models: (1) a generalized additive binomial model to forecast the probability of congestion and (2) state-space models of speed and flow. The state-space models use a dynamic linear model (DLM) with switching structures to describe the bimodal distribution of speed and flow in the free-flow and congested states. Model selection, parameter estimation and checking are presented.

Although advanced technologies, such as detection techniques and controllers, have been incorporated within Advanced Traffic Management Systems (ATMS), pretimed signal control still plays an important role in traffic control and management. A wide variety of techniques were proposed to generate optimal or near-optimal solutions for signal optimization problems. However, only a limited research was devoted to the application of tabu search in the signal optimization problem. The characteristics of tabu search could provide accuracy and efficiency with the careful design of local search methods. This research applies a randomized meta-heuristic algorithm, greedy randomized tabu search (GRTS), for network-level signal optimization problems. With the flexibility of the GRTS, detailed representations of signal control settings could be added easily. To compare the performance of GRTS with other algorithms, genetic algorithm (GA) is chosen and implemented. The performance of the GRTS is investigated in numerical analysis in two networks, including a test network and a real city network. Numerical experiments on the test network are used in the comparison of the GA and GRTS algorithms. Numerical experiments on the real city network are conducted to illustrate possible benefits from the proposed approach. The results show that more than 25% reduction of travel time can be achieved for medium and high demand levels.

This paper uses an instrumented probe vehicle to monitor ambient traffic and overcome many challenges of observing traffic flow phenomena that occur over extended distances. One contribution of this paper is a general methodology to identify the probe vehicle’s lane of travel without a priori knowledge of where the lanes are. This knowledge is used to find the probe’s lane-change maneuvers (LCMs), to differentiate these LCMs from GPS errors, and, in conjunction with a ranging sensor, to identify which lanes the ambient vehicles are in to find their LCMs. The second contribution of this paper comes from the identified LCMS. The data are used to provide an independent validation of earlier studies, and thus yield further evidence of how LCMs contribute to the formation of disturbances within freeway queues. In particular, it is found that vehicles following an entering vehicle generally complete their response and return to steady state quicker than those following an exiting vehicle. As discussed herein, this asymmetry in the lane-change maneuver accommodation time effectively induces a ripple in the traffic state that propagates upstream. The resulting disturbances provide a possible mechanism to explain the fact that congested traffic tends to fluctuate, e.g., stop-and-go traffic, rather than remain at a single, relatively stable congested state.

This study aims to use the classification and regression tree (CART) approach, one of the most powerful data mining techniques, to predict drivers’ merging behavior in a work zone merging area. On the basis of the eight factors affecting drivers’ merging behavior, a binary CART is built using the merging traffic data collected from a short-term work zone site in Singapore. The CART comprises 7 levels and 15 leaf nodes to predict drivers’ merging behavior in the work zone merging area. The results show that the CART provides much higher prediction accuracy than the conventional binary logit model. Traffic engineers can easily understand how drivers make merging/nonmerging decisions. This demonstrates that the CART approach is a good alternative for investigating drivers’ merging behavior in work zone merging areas.

Reliability-based analysis of road geometric design has been reported in literatures as a trend in transportation safety study. In the reliability analysis of a horizontal curve, the performance function is usually formulated as a function of the failure mode of vehicle skidding only. This paper takes into account the failure modes of vehicle skidding and rollover in formulating the performance functions of cars and trucks, respectively. A comparative study of three different performance functions for calculating the probability of vehicle failure modes is conducted. The results qualitatively show that trucks are more vulnerable to skid than cars, and are more likely to rollover than to skid on dry pavement. A vehicle's is greatly influenced by vehicle suspension and roll motion. A sensitivity analysis investigating the influences of vehicle parameters and superelevation on vehicle skidding and rollover follows. In order to make the paper practically useful, the probability of failure for the minimum radius recommended by AASHTO at various superelevations and design speeds was computed to investigate the reliability of the recommended minimum radius.