A three-dimensional highway alignment optimization methodology is developed that automatically determines whether and where bridges or tunnels are preferable to embankments or deep cuts, respectively. This is done by comparing the optimized costs of such alternatives. The data for detailed computations of earthwork, right-of-way, vehicle operation, user time, and other costs are obtained from a geographic information system (GIS) for each alternative alignment considered. The alignment optimization process relies on a genetic algorithm developed for this problem. Two example studies implemented in an artificial study area with a real GIS show that by modeling bridges and tunnels we can improve the reliability and adaptability of highway alignment optimization as well as find more practical solutions than otherwise.

The standard and modified Proctor compaction tests have been widely used for evaluation of design properties and compaction characteristics of subgrade soils. However, different types of compaction roller equipment, each producing a different level of soil compaction, are used in the field for compaction of subgrade soils. The purpose of this paper is to evaluate the design properties of compacted subgrade soils using the gyratory compactor made by Servopac to simulate field compaction conditions. Field compaction data were collected from a road construction site in Pusan, Korea. After compaction of the subgrade soil in the field using a vibratory roller was concluded, block samples of the subgrade material were collected. Disturbed soil samples were collected for preparation of specimens in the laboratory using the Proctor compaction and gyratory compaction methods. Unconfined compression test results show that the peak strength, cohesion, and elastic modulus values of the specimens prepared from the field block samples and that of the specimens prepared using the Superpave gyratory compactor with a $600\mathrm{kPa}$ vertical pressure are similar. On the other hand, much higher values were obtained for these quantities for the laboratory specimens prepared using the modified Proctor method. Our test results indicate that the evaluation of design properties of subgrade soils based solely on the Proctor compaction tests may not be appropriate.

This paper develops a dynamic prediction model of a highway pavement contractor’s quality-based performance using a panel (longitudinal) data analysis. This panel data modeling uses as-built roughness measurements and pavement and contractor’s characteristics for reconstructed, replaced, and resurfaced pavement projects in Wisconsin from 1998 through 2002. Several random effects models were first developed in in-sample specification, and their modeling performances were measured by Akaike’s information criteria, which combines goodness of fit and model complexity. Out-of-sample specifications validated the developed random effects models by comparing out-of-sample forecasting accuracies. The results show that the best model has approximately a 16% mean absolute percentage error. The results finally show that asphaltic concrete pavement quality of construction can be predicted based on the contractor’s past quality-based performance and other construction parameters. Therefore, the dynamic prediction model developed in this study could be implemented in the contractor’s prequalifications required for advanced contracting methods.

While significant progress has occurred in quantifying congestion costs within the sphere of traffic engineering, little progress has been made to incorporate such costs into network-level highway evaluation systems. The model presented in this paper takes a middle ground approach between the highly detailed microsimulation approach that is most appealing to the traffic engineer and the traditional highway development engineers’ approach of ignoring traffic congestion. The approach adopted is based on modeling of acceleration noise, defined as the standard deviation of accelerations. During periods of high traffic congestion, there is a greater variability in speed, resulting in higher acceleration noise levels. Data collection and analysis have been undertaken on highways in Auckland (New Zealand), Kuala Lumpur (Malaysia), and Bangkok (Thailand). This updated approach (relative to the original HDM-4 research in 1995) has been integrated with the International Study of Highway Development and Management Tools in order to provide an updated model HDM-4 (Highway Development and Management version 4). Fuel consumption predictions were tested both with and without the impact of a simulated acceleration noise level. For the latter of the two (i.e., a given drive cycle) the predictions were within 0.25%. For a generated drive cycle, the results show a consistent underprediction of some 25%. It is believed that this underprediction is largely due to the assumption of the acceleration noise data conforming to a normal distribution. While not prescribed in detail within this paper, vehicle emission models were also developed as part of the work with the results of tests presented. Vehicle emissions of carbon dioxide and hydrocarbons were within the range of the seven vehicles observed. Carbon monoxide and oxides of nitrogen were grossly underpredicted and were below the minimum observed values. These latter results are thought to be caused by the fuel model not predicting rich operating conditions during periods of high acceleration. The model presented, even with the preceding limitations, still has wide application in improving the prediction of vehicles operating on highways in congested conditions. In particular, the model presented provides a much improved predictive ability over those of traditional speed-flow approaches, where errors as high as 200% for passenger cars (higher for trucks) are observed. This makes the approach highly appropriate for inclusion into highway evaluation procedures such as HDM-4. The patterns of fuel consumption and emissions show the appropriate changes in relation to traffic congestion. Furthermore, the model framework readily lends itself to enhancement via adoption of new submodels.

Most thermoplastic pipes exhibit peaking behavior during the initial backfilling process. It is shown with the actual field data that the peaking deflections can be beneficial for minimizing the long-term deflections of the pipe. An approach similar to the one proposed by Spangler is used to derive a formula for estimating the peaking deflections of thermoplastic pipe due to forces generated during the initial backfilling. The formula is tested in light of a number of field installation cases. The results show that the proposed formula predicts peaking deflections of both polyvinyl chloride and high density polyethylene pipes accurately under a variety of backfilled conditions.

Treatment selection bias leads to an inaccurate estimation of treatment effects as applied to specific sites or problem locations. Treatment selection bias is a major source of inconsistency in the results obtained from conventional before and after and cross-sectional models. One of the major expressions of treatment selection bias concerns the use of collision occurrence data in justifying intervention. For example, in highway safety field, a treatment is often introduced at a given site based on its high collision experience. Under normal conditions we would expect these collision numbers to return to a lower long term expected value, regardless of intervention. For treated sites, conventional observational models ascribe this reduction in collisions to the given treatment. This results in an overestimation of treatment effect. In this paper, a propensity score model is introduced that deals explicitly with treatment selection bias. The model is applied to Canadian highway–railway grade crossings data to estimate reductions in collision subject to upgrades in warning devices. The results of the propensity score model are compared for similar types of treatments to a number of before and after and cross-sectional models for both U.S. and Canadian data. The propensity score method is shown to reduce treatment selection bias and has probable merit that need to be further examined.

A heuristic approach to the application of bandwidth-oriented signal timing is proposed based on a system partition technique. The proposed approach divides a large signalized arterial into subsystems with three to five signals in each subsystem. Each subsystem is optimized to achieve the maximum bandwidth efficiency. A one-directional system progression bandwidth, normally in the peak-flow direction, is then formed by appropriately adjusting the offsets between each subsystem. Such an approach provides a signal-timing solution that would achieve maximum progression for the peak direction while still maintaining partial progression for the off-peak direction. Further improvements on signal timing may be achieved by adjusting the phasing sequences at the subsystem boundary locations. A case study is presented to illustrate how the proposed approach can be applied, and the timing solutions are compared with the solutions from traditional signal-timing software. Evaluation of the timing solutions using CORSIM simulation indicates that the proposed approach results in improved bandwidth efficiencies for both directions and improved performance measures such as stops and travel speeds. The proposed heuristic approach is easy to apply using existing signal timing software packages such as PASSER II and Synchro. The proposed approach could also be used to develop new or improved existing bandwidth optimization algorithms.

Recently ways of assessing the need for and providing for improved passing opportunities on rural two-lane (single-carriageway) highways has been investigated in New Zealand. This paper focuses on studies of the performance of slow-vehicle bays (SVBs), also known as “turnouts.” Field surveys at eight sites identified the effect of different features on SVB usage and on reduction in following. Higher levels of SVB use than reported overseas were observed; however, this use appears to be very dependent on the location and design of each site. The SVBs’ effects on vehicle following was generally not substantial, although the short-term benefits probably reduce driver frustration. Minimum desirable lengths for SVBs were also reviewed, and it was found that the current New Zealand guidelines for SVB lengths may be inappropriate, given the number of merged area conflicts and multivehicle queues SVBs create on the roads. From these findings, project evaluation methods were developed using simplified analytical procedures and a simulation modeling package.

Tracking vehicles through roundabouts is laborious. Because of this, turning movement volumes are usually estimated using a variety of methods. This paper identifies and evaluates practical methods of estimating turning movement volumes at roundabouts. Thirty four experiments were used to test the effects of different estimation treatments: estimation procedure, time interval size, count location configuration, and turning movement sample procedure. A new economical sampling procedure was introduced and included in the experiment design. The experiments were evaluated using volume estimation and capacity estimation errors. Findings showed that the new sample procedure works well relative to a random sampling procedure. Other insights were gained regarding the four treatments included in the experiment design.