Journal of Transportation Engineering, Part A: Systems

The interaction between deformable tires and pavements was studied using finite-element modeling and a semicoupled approach. Three finite-element models were used: (1) a hyperelastic tire rolling on an infinitely rigid surface; (2) a three-dimensional pavement model; and (3) a hyperelastic tire rolling on a deformable viscoelastic body. The tire and pavement models have been successfully compared with experimental measurements. Tire interaction with a rigid surface provided contact stresses to excite the pavement model, and results of the pavement model defined the boundary conditions of the tire rolling on the deformable body. After that, the pavement loaded with the contact stresses from the tire interacting with the deformable body was run. This study focuses on issues related to pavement damage (tire–pavement contact stresses and critical pavement responses) and lifecycle assessment (rolling resistance). Transverse contact stresses were the most affected by pavement deformation, which translated into impact on the maximum vertical strain and the maximum shear strain in the asphalt concrete layer. The tire moving on a deformable body showed that the thin pavement created a higher rolling resistance force than thick pavements. In addition, dissipation-based and deflection-based approaches for calculating pavement contribution to rolling resistance were equivalent. Finally, for the range of values considered, changes in tire inflation pressure affected the rolling resistance force more than changes in applied load.

The selection of long-lasting and cost-effective rehabilitation strategies is crucial to pavement engineers. Development of rehabilitation and preservation decision trees and support tools that involve performance scores are pursued by agencies across the world. However, for the purpose of rehabilitation selection, pavement scores determined from pavement-distress surveys reveal flaws in capturing pavement needs. This paper introduces a rehabilitation methodology based on the application of a damage ratio estimated from falling-weight deflectometer (FWD) data, and a rutting index determined from a distress survey. A detailed project-level investigation was conducted on a series of flexible and composite (asphalt over an existing portland cement concrete layer) pavement sections from a high-traffic-volume interstate highway network. The study includes the evaluation of existing pavements through back-calculation of FWD data and monitoring field-distress data, conducting asphalt mixture laboratory testing as well as mechanistic–empirical pavement design guide and life cycle cost analysis. The results of analyses are used to develop a robust methodology and a series of time-based rehabilitation strategies for a network of flexible and composite pavement sections located in Oklahoma.

The most recent tendencies in pavement engineering design are directed to the return of the use of fundamental mechanical principles of engineering to predict design life through the concept of damage. Damage is associated with the relation between (1) the number of repetitions a material can resist until failure and (2) the predicted repetitions the designer is expecting during a period of time. Generally, mechanical responses as strains, stresses, and displacements are used to calculate the number of repetitions until a specific failure. In rigid pavements, there are analytical solutions that range from simple Westergaard’s closed-form formulas to complex numerical solutions (as discrete-element methods and finite-element methods). This paper describes work done to develop an additional option in the middle: models calibrated to have the simplicity of the closed-form formulas and the accuracy of the finite-element methodology. Those models were then included in a graphical user interface, which will be used as the structural response engine in local mechanistic-empirical (M-E) design software.

This study utilizes travel time data from a well-equipped Intelligent Transportation System corridor to integrate travel time and traffic signal data with the goal of developing a volume-delay relationship between a signal’s volume-capacity ratio and travel time. Specifically, the traffic signal timings were retrieved from an advanced transportation management system, individual travel time data were extracted from a WiFi-based travel time measurement system, and traffic volumes and queues were obtained by observing closed-circuit television video recordings. The collected data were then integrated on a cycle-by-cycle basis by using a C#-automated data postprocessing interface. Several traditional volume-delay functions were calibrated to fit the field data. Also, a new volume-delay function, named So-Stevanovic Volume-Delay Function, was developed to account for exponential behavior of travel time near and beyond the traffic saturation point. The So-Stevanovic Volume-Delay Function satisfied the seven Spiess’s requirements for a well-behaved congestion function and produced slightly better results than the best traditional volume-delay function. All of the functions were then tested again on a different road segment in order to validate the results. These tests confirmed the previous findings that the So-Stevanovic Volume-Delay Function was the best predictor of relationship between volume-capacity ratio and link travel time. Further research should be conducted to validate this function in a variety of field traffic conditions.

Public transport planners are required to make decisions on transport infrastructure and services worth billions of dollars. The decision-making process for transport planning needs to be informed, accountable, and founded on comprehensive, current, and reliable data. One of the major issues affecting the accuracy of the estimated origin-destination (O-D) matrices is sample size. Cost, time, precision, and biases are some issues associated with sample size. Smart card data can potentially provide much information based on better understanding and assessment of the sample size impact on the estimated O-D matrices. This paper uses South East Queensland (SEQ) data to study the effect of different data sample sizes on the accuracy level of the generated public transport O-D matrices and to quantify the sample size required for a certain level of accuracy. As a result, the total number of O-D trips for the whole network can be accurately estimated at all levels of sample sizes. However, a wide distribution of O-D trips appeared at different sample sizes. The large difference from the actual distribution at 100% sample size was readily captured at small sample sizes where more O-D pairs were not representative. The wide distribution of O-D trips at different levels of sample sizes caused significant errors even at large sample sizes. The variation of the errors within the same sample was also captured as a result of the 80 iterations for each sample size. It is concluded that three major parameters (distribution, number, and sample size of selected stations) have a significant impact on the estimated O-D matrices. These results can be also reflected on the sample size of the traditional O-D estimation methods, such household travel surveys.

The impacts of road congestion charges on traffic safety are often overlooked in evaluating the benefits of congestion charging practices and searching for traffic safety strategies. This paper aims to examine how congestion pricing affects both efficiency and automobile safety. The first part of the study proposes and formulates the general traffic accident minimization pricing (TAMP) problem. Considering within-day and day-to-day travel demand fluctuations, a multiobjective bilevel optimization model under stochastic travel demand is developed based on the TAMP problem. This model is employed to determine the optimal toll levels that minimize both the negative externalities of congestion and accidents. Numerical results indicate that the traditional efficiency-oriented congestion pricing scheme, which does not consider impacts to safety, is often implemented in a less beneficial manner with regard to accident reduction.