John E. Haddock

A study of factors affecting highway accident rates using the random-parameters tobit model.

A large body of previous literature has used a variety of count-data modeling techniques to study factors that affect the frequency of highway accidents over some time period on roadway segments of a specified length. An alternative approach to this problem views vehicle accident rates (accidents per mile driven) directly instead of their frequencies. Viewing the problem as continuous data instead of count data creates a problem in that roadway segments that do not have any observed accidents over the identified time period create continuous data that are left-censored at zero. Past research has appropriately applied a tobit regression model to address this censoring problem, but this research has been limited in accounting for unobserved heterogeneity because it has been assumed that the parameter estimates are fixed over roadway-segment observations. Using 9-year data from urban interstates in Indiana, this paper employs a random-parameters tobit regression to account for unobserved heterogeneity in the study of motor-vehicle accident rates. The empirical results show that the random-parameters tobit model outperforms its fixed-parameters counterpart and has the potential to provide a fuller understanding of the factors determining accident rates on specific roadway segments.

A multivariate tobit analysis of highway accident-injury-severity rates

Relatively recent research has illustrated the potential that tobit regression has in studying factors that affect vehicle accident rates (accidents per distance traveled) on specific roadway segments. Tobit regression has been used because accident rates on specific roadway segments are continuous data that are left-censored at zero (they are censored because accidents may not be observed on all roadway segments during the period over which data are collected). This censoring may arise from a number of sources, one of which being the possibility that less severe crashes may be under-reported and thus may be less likely to appear in crash databases. Traditional tobit-regression analyses have dealt with the overall accident rate (all crashes regardless of injury severity), so the issue of censoring by the severity of crashes has not been addressed. However, a tobit-regression approach that considers accident rates by injury-severity level, such as the rate of no-injury, possible injury and injury accidents per distance traveled (as opposed to all accidents regardless of injury-severity), can potentially provide new insights, and address the possibility that censoring may vary by crash-injury severity. Using five-year data from highways in Washington State, this paper estimates a multivariate tobit model of accident-injury-severity rates that addresses the possibility of differential censoring across injury-severity levels, while also accounting for the possible contemporaneous error correlation resulting from commonly shared unobserved characteristics across roadway segments. The empirical results show that the multivariate tobit model outperforms its univariate counterpart, is practically equivalent to the multivariate negative binomial model, and has the potential to provide a fuller understanding of the factors determining accident-injury-severity rates on specific roadway segments.

METHOD TO ENSURE STONE-ON-STONE CONTACT IN STONE MATRIX ASPHALT PAVING MIXTURES

The use of stone matrix asphalt (SMA) has continued to rise in the United States because of its ability to withstand heavy traffic without rutting. This ability is derived from a stone-on-stone coarse aggregate skeleton. While this coarse aggregate skeleton is imperative for SMA to perform, no quantitative method exists to measure it. A method for determining when stone-on-stone contact exists is presented. The proposed method first determines the voids in the coarse aggregate (VCA) for the coarse aggregate–only fraction of the SMA mixture. Second, the VCA is determined for the entire SMA mixture. When the two VCA values are compared, the VCA of the SMA mixture should be less than or equal to the VCA of the coarse aggregate–only fraction to ensure that stone-on-stone contact exists in the mixture. Five different methods for determining the VCA of the coarse aggregate–only fraction were used to see which performed best and was the most practical. The aggregate degradation produced by each of the five methods was also determined and compared with the coarse aggregate breakdown produced in an SMA mixture compacted with 50 blows of a Marshall hammer. The results indicate that the Superpave gyratory compactor and dry-rodded methods produced the best results. Both methods are recommended for further testing.

Household Automobile and Motorcycle Ownership Analyzed with Random Parameters Bivariate Ordered Probit Model

This paper investigates the factors that affect household automobile and motorcycle ownership in large metropolitan areas. Extensive geocoded trip data from Athens, Greece, were modeled with the random parameters bivariate ordered probit model. This model accounts for unobserved heterogeneity in the data population and commonly shared characteristics with automobile and motorcycle ownership. The random parameters bivariate probit model provided a statistically superior fit compared with its fixed parameters counterpart. The studys results indicate that vehicle (automobile and motorcycle) ownership is determined by a number of factors, such as traveler characteristics, the population density at the origin and destination, the distance and time to the destination for several trip purposes, and access to public transit.

Random Parameters Seemingly Unrelated Equations Approach to the Postrehabilitation Performance of Pavements

Pavement rehabilitation is one of the most critical and costly forms of infrastructure asset management. Yet determining the subsequent performance of rehabilitated pavements is a complex task, particularly when multiple performance measures such as roughness, surface deformation, and structural integrity are considered. The complexity arises in part because of the interrelation among these performance measures and the fact that data relating to factors known to affect these measures may not be available. This paper seeks to demonstrate an appropriate methodological approach for studying the postrehabilitation performance of pavements using data from rural interstate roads in Indiana. Specifically, a random parameters seemingly unrelated equations approach is applied to explicitly account for the cross-equation correlation that exists among pavement-performance measures and the underlying heterogeneity across observations caused by imperfect data. The results provide some new insights into the interrelationships among the pavement rehabilitation treatments considered, pavement performance, traffic loads and trucks, weather and soil conditions, and rehabilitation expenditures.

INVESTIGATION OF STONE MATRIX ASPHALT MORTARS

The use of stone matrix asphalt (SMA) has continued to increase in the United States since its initial application in 1991. This preference for SMA has been linked to its ability to withstand heavy traffic without rutting. The antirutting capability of SMA is normally accredited to the presence of a stone-on-stone aggregate skeleton in the mixture. However, the mortar in an SMA mixture is also important. The mortar is composed of fine aggregate, filler, asphalt cement, and a stabilizing additive. Work to characterize SMA mortars is detailed. For testing purposes, the mortar was broken into separate phases, total mortar and fine mortar. The fine mortar was tested using the Superior Performing Asphalt Pavements system (Superpave) binder tests. The total mortar was tested using the bending beam rheometer, resilient modulus, indirect tensile test, and Brookfield viscometer. The results indicate that the fine and total mortars are closely related. In addition, it was determined that at least some of the Superpave tests can be used to characterize SMA mortars. It is recommended that further testing be completed and specification criteria be established for the mortar.

Structural Adequacy of Rubblized Portland Cement Concrete Pavement

The objective of rubblization is to eliminate reflection cracking in hot-mix asphalt (HMA) overlay by the total destruction of the existing slab action. Rubblization is applicable when there is little potential for retaining slab integrity and structural capacity of the original jointed reinforced concrete pavement. Rubblization has been used successfully for rehabilitation of other portland cement concrete (PCC) pavement types. Typically, the slab is reduced to pieces less than 300 mm in size. Subsequently, the slab is converted to a high-strength granular base. Restoration of the structural capacity is accomplished with an overlay of HMA. In 1991, the Indiana Department of Transportation (INDOT) awarded a contract to apply the rubblization technique to a portion of US-41 in Benton County. The pavement sections were evaluated before and after rubblizing and overlay to estimate the AASHTO layer coefficient of rubblized concrete pavements. The layer coefficient determined in this study (a2 = 0.25) represents a value of two standard deviations less than that reported by PCS/Law. Currently, INDOT uses a layer coefficient of 0.20 for rubblized PCC pavements. On the basis of the results of this study, the layer coefficient can be set within two standard deviations of the mean (i.e., 0.22). This layer coefficient of 0.22 represents a conservative value that is recommended for rubblized PCC pavements with similar conditions. If INDOT continues to use the rubblization technique in pavement rehabilitation, a study encompassing slabs of different thicknesses on different subgrades should be undertaken for confirmation of the values that are reported herein.

An object-oriented framework for finite element pavement analysis

In this study, we developed an object-oriented (OO) framework with interactive graphics to assist pavement studies using finite element analysis (FEA). FEA has been proven to be effective in studying various pavement failure problems; however, it is time consuming and error prone to manually generate the load sequences where non-regular tire footprints, non-uniform tire-pavement contact stresses, and transverse wheel wander distributions are used. After FEA, extracting the deformations for failure analysis is necessary but tedious. The OO framework developed in this study handles the preprocessing and postprocessing tasks for the FEA of pavements. It has a graphical user interface and is platform independent. It was successfully used in developing a new criterion for characterizing pavement failures that involved approximately four hundred different FEA simulations.

Cost Overrun in Public-Private Partnerships: Toward Sustainable Highway Maintenance and Rehabilitation

AbstractTransportation agencies worldwide have been preparing themselves to face the growing demand for transportation infrastructure by forming public-private partnerships (PPP), contractual agreements formed between public and private sector entities, to allow for greater private sector participation in the delivery of transportation projects. However, there is one major concern that needs to be addressed: the issue of accurately estimating maintenance and rehabilitation costs at the project planning stage. The accuracy of these estimates plays a significant role in determining project characteristics, and in selecting appropriate projects and PPP approaches for implementation, so that they may lead to sustainable highway preservation strategies. This paper compares the contract winning bid cost with the final as-built cost of highway maintenance and rehabilitation projects, determines possible cost overruns across the projects and identifies influential factors that affect them. The analysis is perform...

HMA Pavement Performance and Durability

It has long been argued that at densities higher than approximately 92 percent (air void contents lower than 8 percent), a hotmix asphalt mixture is impermeable to water. However, as densities become lower (air void contents higher) than this, small decreases in the density can yield exponential increases in permeability. The objectives of this study were to better understand the increases in hot-mix asphalt pavement performance and durability that can be gained by increasing the initial pavement density and to better quantify the inter-relationship among pavement density, permeability, and moisture-induced damage. The long-term performance and durability of four hot-mix asphalt mixtures at four different air void contents were evaluated with the dynamic modulus and beam fatigue apparatus. The mixtures differed in both aggregate size and gradation. In order to evaluate durability effects, performance tests were performed on unconditioned, moisture conditioned and ovenaged samples. The results indicate that density (air void content) is a significant factor in the performance and durability of hotmix asphalt mixtures. Its effects vary with aggregate size and gradation, but increases in mixture density (reductions in air voids content) produce improvements in the dynamic modulus (reduction of rutting potential) and fatigue life of a mixture. Further, the fatigue life appears to be less sensitive to density (air voids content) than to moisture damage.