Existing state-of-the-practice traffic signal timing-optimization programs rely on macroscopic and deterministic models to represent traffic flow, including coordinated actuated traffic signal systems. One distinct shortcoming of such an approach is its inability to account for the stochastic nature of traffic, such as the variability in traffic demand, driver behavior, vehicular interarrival times, vehicle mix, and so forth. In addition, the existing traffic signal timing-optimization programs for coordinated actuated traffic signal systems still focus on four basic traffic signal timing parameters (i.e., cycle length, green times or force-off points, offsets, and phase sequences). Studies have shown that actuated signal settings such as minimum green time, vehicle extension, and recall mode are also important parameters in traffic signal operations. This study presents the development of a stochastic-optimization method for coordinated actuated traffic signal systems. The proposed method accounts for stochastic variability by using a well-calibrated microscopic simulation model, CORSIM, instead of a macroscopic and deterministic model, and it simultaneously optimizes actuated signal settings and the four traffic signal timing parameters by adopting a genetic algorithm with special decoding schemes. The proposed method was applied to a real-world arterial network in Charlottesville, Virginia. The performance of the proposed method was compared with that of an existing traffic signal timing-optimization program, Synchro, using a well-calibrated microscopic simulation model, VISSIM. The results indicated that the proposed method outperforms the existing timing plan and the Synchro-optimized traffic signal timing for the tested arterial network.

This study aimed at developing a new approach for analyzing life-cycle costs for road barriers during the road planning and design process. A method called Activity-Based Life-Cycle Costing using the Monte Carlo Simulation was used to analyze and calculate the life-cycle costs. The results show a potential for increasing efficiency throughout the road planning and design process by minimizing the life-cycle costs of road components. The results also show that implementation of life-cycle cost analyses in the road planning and design process is possible, but difficult, mainly due to lack of relevant data.

This paper highlights the left-turn waiting area in an intersection and proposes a different perspective for measuring the capacity of the traffic flows, which permits the through vehicles to queue on the left lane in a protected signal operation. The effect of flow diverting from the through lanes on the left lane is quantitatively analyzed with random service system theory and probability theory. The utilization of the left-turn waiting area significantly improves the discharge rate of the through lane without compromising the efficiency of left-turning flows, thus reducing the average vehicle delay. A typical intersection with a different capacity of left-turn waiting area is presented to verify the advantage of shared-use operation in the average delay. Besides, effects of the length of the left-turn waiting area, green ratio, and left-turn proportion on the capacity in shared lane are constructed in different conditions. The relationships between these parameters and the actual capacity are presented to show the trade-off between shared use and the exclusive configuration. Theoretical analysis and simulation results show that the shared-use style still works even when the arrival rate of through flows reaches the road capacity, which may result in congestions.

In a discrete network design problem, an optimal subset is chosen from a set of proposed link additions to an existing road network in order to minimize the total cost of users. The problem has been called as a complex issue in the transportation planning literature. The main source of complexity is that the problem is a bilevel program in which the lower-level program is a traffic assignment problem. In this paper, a path-based traffic assignment problem is used as the lower-level problem. The path-based algorithms not only provide the link-flow solution, but also the useful path-flow solution (path information) that may be required or used in certain applications, such as network design problem. To solve a network design problem, the traffic assignment problem will need to be solved many times. The main objective of this paper is to expedite the solution of the network design problem by initializing traffic assignment problems with path sets already found in previously performed traffic assignments. The rationale behind this idea is that the addition of a number of proposed links to a network will not change the used paths for the majority of origin-destination (OD) pairs. In this paper, the network design problem is solved by a branch and bound algorithm for a small network and a relatively large network. It is shown that the proposed method is capable of reducing the computation time to one-fifth in real-size networks.

Loop detectors are the most commonly used vehicle detector for freeway management. A loop detector consists of a physical loop of wire embedded in the pavement connected to a sensor located in a nearby cabinet. The sensor detects the presence or absence of vehicles over the loop and typically allows a user to manually select the sensitivity level of operation to accommodate for a wide range of responsiveness from the physical loop. In conventional practice, however, it is difficult to know the physical loop’s responsiveness, which makes selecting the appropriate sensitivity level difficult. If the sensitivity and responsiveness are poorly matched it will degrade the detector’s data and the performance of applications that use the data, including: traffic management, control, and traveler information. To resolve this often overlooked problem, this paper presents an algorithm to assess how well a loop detector’s sensitivity is set by calculating the daily median on-time from the data reported by the loop detector. The algorithm can be incorporated into conventional controller software or run off-line. The result can be used both to correct the detector on-times for an inappropriate sensitivity setting in software (e.g., through a multiplicative correction factor) and to trigger an alarm to dispatch a technician to adjust the hardware sensitivity. Plotting the daily median on-time over months or years can show how the detector performance evolves. The approach is then transposed to dual-loop detectors to identify and correct for inaccurate spacing between the paired detectors. Finally, the methodology is evaluated by comparing the loop detector speeds against the concurrent velocities from a GPS-equipped probe vehicle. Although the focus of this paper is on loop detectors, with only minor modification the algorithm should also be applicable to other detector technologies that emulate loop detector operation, e.g., side-fire microwave radar.

This paper presents a method to evaluate the operational effects of managed lane policies—vehicle eligibility, access control, pricing, and the number of managed lanes—that form a policy combination set. Two macroscopic methods are developed to prescreen the set via simple criteria, followed by integer linear programming with multiple objectives and constraints to identify the noninferior policies among the downsized set. The approach is demonstrated on the Southern California SR-57 corridor. The application eliminates twelve of possible twenty policy combinations by the macroscopic methods, and generates four noninferior policies—the existing high-occupancy vehicle lane operation and three additional potential high-occupancy toll lane policies—in terms of maximum vehicle and passenger throughput, minimum vehicle hour traveled, and travel time variance. The prescreening efficiency of the macroscopic stage, ranging from 0 to 95%, is affected by the initial policies and traffic conditions. It is concluded that the approach can substantially assess a larger policy set and effectively identify the operational effects of joint manage lane policies.

With the current demand for portland cement concrete (PCC) sustainability, supplementary cementitious materials (SCMs) are often used in concrete mixtures to improve the mixture properties in both fresh and hardened concrete. In this research, sixteen concrete mixtures (one control mixture, three binary mixtures, and twelve ternary mixtures) with various combinations of fly ash, slag, and portland cement were fabricated. The thermal and mechanical properties of the selected ternary mixtures were measured at various ages, and the critical temperature gradient through the slab thickness was generated by using the enhanced integrated climatic model (EICM). By using the measured mechanical properties, nonlinear temperature gradients obtained from EICM, and CTE gradients throughout the slab thickness, Westergaard-Bradbury solution was used to calculate the critical tensile stress on the PCC pavements. The analysis results show that all the ternary mixtures with the replacement of 30% slag and 30% fly ash, and replacement of 50% slag and 20% fly ash did not exceed 100% tensile stress-to-strength ratio at all ages.

The role of filler on the mechanical performance of asphalt-concrete mixture was investigated. Three wearing course (W3B) mixtures incorporating granite, hydrated lime, and kaolin as filler fractions were evaluated by the Marshall mix design method to determine their optimum asphalt content. The use of hydrated lime or kaolin as a filler requires more asphalt because of their relatively higher specific surface area. The highest stiffness performance was found for W3B-hydrated lime, followed by W3B-granite, and W3B-kaolin mixtures. W3B-hydrated lime and W3B-kaolin mixtures exhibited higher deformation resistance than that of W3B-granite mixture. The results showed that the presence of filler in an asphalt-concrete mixture affects the mixture’s performance in three ways: filler influences the amount of asphalt content, filler affects the workability during mixing and compaction, and the resultant properties of asphalt-filler mastic contribute to the mixture’s performance. The results show that the properties of the filler determine its interaction with asphalt and its contribution to the mixture’s performance.

In Portugal, as in many other countries, due to the economic crisis, the trend of budgetary pressures on highway agencies is increasing. At the same time, road users are increasingly demanding in terms of highway quality, comfort, and safety. Several highway projects have been delayed because of budget constraints. To meet these challenges highway agencies are looking for more cost-effective methodologies for pavement management at project-level. This paper presents a new pavement design optimization model, called OPTIPAV, which considers pavement performance, construction costs, maintenance and rehabilitation costs, user costs, the residual value of the pavement at the end of the project analysis period, and preventive maintenance and rehabilitation interventions. It was developed and programmed to help pavement designers to choose the best pavement structure for a road or highway. The results obtained by the application of the new pavement design optimization model clearly indicate that it is a valuable addition to the road engineer’s toolbox.

State highway agencies concerned with lower asphalt levels and potential durability problems in hot-mix asphalt (HMA) mixtures designed with superior performing asphalt pavements (Superpave) have lead efforts to explore strategies for improving Superpave mix design. This study addressed the differences in HMA properties that have been observed over the years between samples taken at the plant versus behind the paver for Superpave designed mixtures in Maryland. A large set of Maryland State Highway Administration (MSHA) quality assurance (QA) and quality control (QC) data were analyzed statistically in the context of current specifications. Statistical analysis found that the means and standard deviations of the QC and QA data represent different populations. Because the material leaving the asphalt plant is the same material that is compacted behind the paver, some relationship between the plant and field properties is expected. However, attempts to define transfer functions between QA and QC measurements to use both data sets in HMA acceptance testing encountered low levels of statistical significance.

Smooth transitions are necessary to ensure the desired ride for the traveling public. Transitions are used within projects as new pavement approaches a bridge to avoid adding unnecessary dead load on the bridge. As roadways pass beneath bridges, transitions are used to avoid encroaching on the existing vertical clearance. This paper describes Virginia Department of Transportation (VDOT) efforts to develop an effective standard for transition details. An in-depth analytical model considering the vehicle dynamics was developed to establish the transition lengths for various overlay thicknesses and speed limits. Virtual profiles using these lengths and overlay thicknesses were generated to assess the ride over the transition. Simplified methods to calculate transition lengths were introduced.

The purpose of evaluating mutually exclusive alternatives is to select the one with the most benefits for implementation. A number of analytic techniques are available for such evaluation purposes. This paper discusses four such techniques: cost effectiveness $\mathrm{C}/\mathrm{E}$, benefit-to-cost ratio $\mathrm{B}/\mathrm{C}$, internal rate of return (IRR), and payoff period (PP), including their theoretical foundation and data requirements. Also discussed are the measures of effectiveness (MOEs) associated with each of these techniques and how they are to be interpreted. Alternatives to be selected for implementation following such evaluation can typically be funded under different policy objectives. This paper identifies three such objectives: Objective A, constrained resource perspective; Objective B, investment perspective; and Objective C, face-value perspective. The possible relationship between the alternative selection and the program is discussed in the paper. A case study for a set of six mutually exclusive highway safety alternatives is presented using the four analytic techniques and three objectives, resulting in various possible solutions. Results show that under compatible assumptions, and for a given policy objective, the outcome of the evaluation is not affected by the choice of the analytic technique. However, for a given analytic technique, the outcome may be affected by the choice of the policy objective chosen. The principles presented are relevant for most public projects (e.g., transit, airports) involving the investment of taxpayer resources, even though the case study involves a highway safety project.

In this paper, a new promising variable screening technique is proposed to select important covariates and to improve crash prediction; the group least absolute shrinkage and selection operator (GLASSO). The GLASSO’s main power lies in its ability to deal with data sets havinga large number of categorical variables, the case in this study. Identifying the significant factors affecting the safety of unsignalized intersections was also an essential objective. Two applications of GLASSO were investigated: before fitting the negative binomial (NB) model, and before fitting the promising multivariate adaptive regression splines (MARS) technique using extensive data representing 2,475 unsignalized intersections. Regarding the NB models, GLASSO yielded close prediction capability to the backward deletion and random forest techniques. Also, MARS model fitting after using GLASSO relatively outperformed that after using random forest, with similar prediction performance. Because of its outstanding performance with categorical variables and its simplicity, GLASSO is recommended as a promising variable selection technique. Some significant predictors affecting unsignalized intersections’ safety were traffic volume on the major road, upstream and downstream distances to the nearest signalized intersection, and median type on major and minor approaches.

Railways around the world are experiencing growth in traffic demand and the need to expand their network and line capacity. To accommodate the substantial demand, the conventional railway operator in Taiwan, the Taiwan Railways Administration (TRA), is interested in understanding the potential benefit of adopting various advanced signaling systems, such as hybrid or moving-block systems. In this study, the authors developed a set of analytical capacity models for conventional rail operations with advanced signaling systems, which were implemented in the busiest corridor in the TRA system. The empirical results show that advanced signaling systems generally have positive capacity effects. However, the benefit may not be substantial due to constraints from the station track layouts. Therefore, possible capacity improvement alternatives, such as improving track layouts and upgrading signaling systems, should be considered together to determine the optimal capacity improvement plan. The use of these proposed capacity models can help railway agencies with similar operational environments in their capacity management and resource planning projects.