Although many traffic circles have been designed in Turkey, in recent years few studies have been made on the capacity and performance of roundabouts. In practice, two major problems at intersections need to be solved: traffic accidents and limited intersection capacity. With this in mind, the applicability of various capacity models for single-lane roundabouts to six selected roundabouts in Izmir, Turkey, is discussed. The results show that the HCM2000 procedure can be used as an effective tool for an initial prediction of single-lane roundabout capacity if the lower and upper boundary limits are calibrated. But, since the research was conducted with limited data, the accuracy of the results should be tested with more data sets. Further studies should be conducted to develop a more reliable capacity and performance analysis procedure, especially for Turkey.

One of the main safety factors in merging areas and at skewed intersections is lateral visibility. Two field studies have been conducted to investigate both the vision angles from rear-view mirrors and the dimensions of the best-selling cars in Spain. The impact of the available lateral visibility in merging areas and at skewed intersections has been evaluated, and safe skew angles at both locations have been proposed. A minimum direct field of vision of 220° for drivers was assumed, while design vehicle dimensions were determined from measurements. Then, a skewed intersection that offerred an adequate intersection sight distance was determined. Taking into account the experimental lateral visibility design angles and the dimensions of the design vehicle, a new design has been proposed for merges during which no vehicle can be found in the driver’s blind spot. Another model was proposed for safe lane changing. Minimum angles of vision for the left and right rear-view mirrors in lane changing were determined to avoid the presence of vehicles in the driver’ blind spot.

Improved highway networks result in net benefits to society, of which the reduction in travel time is one of the most important. Similarly, the delay in travel due to construction and maintenance operations represents a real cost to users. Assignment of the value of time in the cases of both benefit and cost involves judgment, as individuals value time differently and adjust for travel time changes in various ways. Values based on wage rates traditionally have been used because they are convenient, but an alternative approach based on purchase of leisure time is proposed. A full life-cycle cost assessment of a project requires an evaluation of future savings in travel time projected over a project’s lifetime, as well as delay costs associated with construction and subsequent maintenance operations. Due to the economic, as well as social complexity of user travel time, alternative measures of valuation and its network effects need to be considered.

While there has been a great deal of research conducted on concrete pavement performance and deterioration under static loads, only very limited research has been carried out on its dynamic response. Furthermore, opinions differ as to which type of loading (static or dynamic) results in greater values of slab deflection or flexural stress. In the present study, a test section consisting of two jointed reinforced concrete pavement and two jointed plain (unreinforced) concrete pavement was constructed and tested under both quasistatic and dynamic truck loads. Truck load was allowed to wander at predetermined locations on the instrumented pavement at speeds from $5\text{to}55\mathrm{km}∕\mathrm{h}$ . Strain gauges and displacement transducers were installed along the test section to monitor the pavement responses. Time history responses of the test section were recorded and used to validate a finite-element model developed in the ANSYS platform for further sensitivity study on those parameters affecting the dynamic response of concrete pavements. Results indicate the significance of dynamic amplification in concrete pavement design.

We discuss Bayesian degradation models that were developed for flexible pavements based on accelerated pavement testing with the heavy vehicle simulator. The models are fitted to data from the Florida Department of Transportation, where rutting performance of three binder types was tested under three temperature settings. The analysis utilizes Bayesian linear mixed-effects models for longitudinal degradation data where the parameter estimates and their posterior marginal distributions are obtained via a Markov chain Monte Carlo (MCMC) technique. The linearity in this model is achieved by utilizing a covariate-dependent Box-Cox transformation of the response variable, where the transformation parameter is estimated as part of the modeling procedure. The paper illustrates the various forms of useful inference that can easily be obtained via the output from the MCMC chains and provides insights regarding the accelerated test experiment at hand. As expected, the results suggest that rut depth development is affected both by the binder type, as well as the test temperature. What is more, the conditional inference made possible by the Bayesian approach utilized here clearly demonstrates the dependence of the inference for the covariate effects on the value of the Box-Cox transformation parameter. Hence the transformation of the response variable is an important step in model building that has to be carefully considered.

This paper reports the results of a chip seal research project in Texas where the researchers are using both quantitative and qualitative means to evaluate chip seal performance on rural roads. The team is making specific use of the Transit New Zealand (TNZ) T/3 “sand circle” test to measure the change in average texture depth over time and applying those measurements to the TNZ P/17 performance specification for allowable surface texture deterioration over the first year of chip seal performance. The results demonstrate the value of quantitatively characterizing the preseal surface condition as a benchmark against which to compare new chip seal performance. Those roads that had poor preseal surface conditions as exhibited by low macrotexture as measured by the T/3 sand circle test showed early loss of macrotexture and premature flushing after a new seal had been applied and failed the specified P/17 1-year texture loss performance criteria. Thus, the paper concludes that not only is having a quantitative metric essential to be able to accurately assess the performance of new seals but also that the use of the TNZ T/3 sand circle test furnishes an easy, cost-effective means to quantitatively characterize preseal surface texture.

Axle load spectra have been used to develop the mechanistic-empirical pavement design guide (M-E PDG). Use of these load spectra provides a more direct and rational approach for the analysis and design of pavement structures to estimate the effects of actual traffic on pavement response and distress. However, the demand for specific truck- and axle load-related data makes the collection of axle load spectra a very complicated, costly, and labor-intensive operation. Due to limited resources available in state and local highway agencies for traffic data collection, the M-E PDG allows for various levels of traffic data collection and analysis. These levels vary from site-specific (Level 1) to regional average (Level 3) traffic load and volume data. This paper explores the possibility of extracting axle loads from truck weight and volume data and presents a practical method of modeling axle load spectra. Axle load-related data used in the analyses cover diversified geographical locations in the United States. The results show that truck weights and proportions on a highway can be used to estimate individual axle load spectra for various axle configurations. The practical implication of these results is that truck weights, which can be measured easily or estimated from existing data, can be related to the axle loads if accurate and rational models are developed for a region based on the local truck traffic characteristics and weights. Such estimates will be superior to assuming a Level 3 input for axle load spectra in the new M-E PDG.

This note establishes the relationship between the surface distress of an asphalt pavement and its roughness, as conveyed respectively by the pavement condition index (PCI) and the international roughness index (IRI). The DataPave software provides the roughness of varied roadway pavement sections from the North Atlantic region that were investigated under the long term pavement performance (LTPP) study. The MicroPAVER1 software system computes the condition of the same sections using cross-referenced distress data from DataPave. A transformed linear regression model predicts pavement condition given roughness. It confirms the acceptability of the IRI as a, albeit not the sole, predictor variable of the PCI whereby the former accounts for the majority, close to 59%, of the variations in the latter. Further, an analysis of variance confirms the existence of a strong relationship between both variables.