A great deal of research has been conducted on Central Florida toll roads to better understand the characteristics of the tolling operation. In this paper, the use of the toll plaza queuing model SHAKER is calibrated to replicate real life toll facility traffic conditions. SHAKER is a deterministic queuing model based on classical physics equations that determines a plaza’s maximum hourly throughput by assigning vehicles to lanes based on queuing conditions. An extensive field study on the Florida’s Turnpike Enterprise network is conducted to determine the parameters affecting toll lane capacities. Data including traffic characteristics, vehicle characteristics, and toll plaza characteristics was collected and extracted at different toll locations, configurations, and pricing. From this data, periods of constant queuing were pinpointed and from those periods, factors such as demand, throughput, service time, etc., were extracted. Using the extracted parameters, SHAKER was then calibrated and validated to estimate the capacity of four different toll plazas along the Florida Turnpike Network.

Recent health and exposure studies have indicated that emissions and air quality standards of particulate matters (PM) numbers could be beneficial since they account for the more harmful ultrafine particles that have negligible mass. This study examines existing modal emission modeling approaches [e.g., polynomial regressions, fuel rate-based approach, and vehicle specific power (VSP)-based approach] in order to evaluate their ability of predicting diesel particle number concentration emitted from a transit diesel bus. This is a necessary and useful first step to quantifying vehicular emissions in terms of PM number. The existing modeling approaches were applied to and then the technique of bootstrapping was used on the onboard measurement data of PM number concentrations emitted from a diesel transit bus. The predictive ability of the models with respect to particle number concentration is assessed by examining the statistical significance of the key regressors used in those approaches and the adjusted $R$ -squared values of the models. Results indicate less than satisfying predictive capability of the examined approaches for PM number emission that behaves in a different manner from gaseous emissions. The study, however, demonstrates that vehicle operating factors such as VSP, speed, and acceleration are significant in explaining the variability of transient PM number concentration measurements from the bus.

A method is presented by which traffic flow estimation between known origins and destinations can be evaluated based on a modified entropy model, and by which bus-routing optimization can be performed. The traffic flow analysis is performed by use of an entropy-based formulation of the vehicular movements of students within the domain under examination, while the perceived level of disorder caused by the numerous vehicle-student-trips in the domain under examination is subsequently used for the formulation of a policy and a bus-routing scheme in order to minimize the original entropy in the system. The entropy metric used in the scheduling optimization is related to the probability of student-trips by origin and destination, and an application of the method is illustrated via a case study of an urban university (with facilities in multiple locations) initiating bus service for its students.

This paper proposes a simple model of regional average congestion delay as a closed-form differentiable function of published regional transportation system volume and capacity. Three initially undefined parameters are calibrated by regression to best match the regional congestion delay estimates of Texas Transportation Institute’s (TTI) “mobility” analysis of 85 U.S. urban regions. The model fits the TTI delay data quite well with goodness of fit parameter $R_a^2=86\%$ and standard error of congestion delay estimate 0.046 min/mi. The model is analytic, that is, differentiable as opposed to discrete data tables. Use of the model is illustrated by closed-form estimates applicable to any urban area with numeric examples of several region descriptive statistics of interest including (1) regional total and average congestion delay for a region not in the TTI ensemble; (2) marginal congestion benefit of freeway lane-mile capacity addition and benefit/cost; (3) capacity addition necessary to improve the region to match congestion delay of the median congested U.S. city (Memphis); (4) “marginal external cost” (delay) of congestion imposed on all other vehicles, per vehicle-mile of added volume; (5) the volume-to-capacity index “point of diminishing return” beyond which further capacity addition would cost more to build than it would return in congestion delay savings and the potential long-term savings of building to that “least total cost” point; and (6) the economic implications of a hypothetical national “build-our-way-out” program which would eliminate all “excess” urban congestion that is costing us more than would the additional capacity to eliminate it.

This paper describes the application of previously developed community-based, macrolevel collision prediction models (CPMs) to evaluate the road safety of a regional transportation plan. The research objective was to present and test model-use guidelines in a regional road safety planning application. The data was extracted from over 400 Greater Vancouver neighborhoods in British Columbia, Canada, including output from the regional transportation model. The CPMs predicted a lower mean collision frequency region-wide due to a proposed three-year transportation plan, versus a do-nothing scenario. Recommendations have been made for future use of the CPMs in regional road safety planning applications. The application of macrolevel CPMs to this regional case study proved a solid step in the development of new and improved empirical tools for planners and engineers to include road safety in the planning process. It is hoped that these models and model-use guidelines will facilitate improved decisions by community planners and engineers, and ultimately, facilitate improved neighborhood traffic safety for residents and other road users.

A methodology is proposed for project-level life-cycle cost analysis of highway intersection safety hardware improvements. It incorporates a disaggregated risk-based approach for computing the safety index that could be used to assess intersection vehicle crash risks affected by the conditions of intersection safety hardware such as signs, signals, lighting, pavement markings, and guardrails. With safety indices estimated before and after implementation of an intersection safety hardware project, the annual potential for safety improvements (PSI) could be computed using the concept of consumer surplus. The annual PSI is further converted into dollar values and extrapolated to the overall intersection safety hardware service life cycle, defined as the useful service life of longest-lasting intersection safety hardware, to determine the maximum project-level life-cycle benefits of intersection safety hardware improvements. A computational study is conducted for methodology application and validation using 5-year data on 226 intersections in Ozaukee County, Wis. The proposed methodology could be adopted by state and large-scale local transportation agencies for intersection safety hardware project evaluation and investment decision making.

In the past, one of the primary focus areas for access management research has been on the physical characteristics of a roadway (i.e., signal spacing, unsignalized access spacing, and median openings) and their associated safety benefits. Although the literature has documented these characteristics as a function of safety, previous research has not investigated the specific relationships between the various other physical characteristics of the arterial roadway network and safety. The objective of this research was to examine the relationships between physical characteristics of the arterial roadway network (including access management related characteristics) and safety. Additionally, a process whereby these relationships could be identified not only for crash rates, but for collision type and crash severity (as a function of crash frequency) was developed. Statistical analyses showed that the specific access management related characteristics were positively related with increased crash rate and severity. Furthermore, land use was identified to play a significant role in the safety of arterial roadways as arterial roadway segments with adjacent commercial land use tended to have higher crash rates and severity.

Fuzzy logic and expert system techniques are effective in evaluating the flexible pavement distress. Distress classification has usually been performed by visual inspection of the surface of the pavement or from the data gathered by automated distress measuring equipment. Consistency in this process can be increased and subjectivity is minimized by using an expert system. A methodology has been developed that uses fuzzy logic for the categorization of distresses. An expert system was developed in $C$ language using fuzzy logic for reasoning. The objective of the developed methodology was to use automated techniques for quick, efficient, and consistent classification for flexible pavement distresses using data from the automated distress measuring system. The developed expert system has been designed to be used as a module within a pavement management system. This will help to completely automate pavement condition evaluation and strategy development for maintenance and rehabilitation of pavements, thus eliminating subjectivity and inconsistency in the process. According to the experts, mostly highway officials, the differences between the actual measured data and results from fuzzy logic expert system approaches were well within acceptable ranges.

Antistrip additives are commonly used to mitigate loss of asphalt-aggregate adhesion, particularly when siliceous aggregates are used in asphaltic concrete mix. Although both liquid antistrip and lime antistrip additives have shown improved “visual based” laboratory results, field performance in Saskatchewan has shown the addition of lime provides improved long term climatic durability and structural performance of asphaltic mixes relative to liquid antistrip additives. As a result, improved laboratory characterization is needed to properly quantify the performance-related properties of these antistrip additives. This laboratory study employed triaxial frequency sweep characterization to determine the effect of hydrated lime antistrip and amine liquid antistrip additives on a standard Saskatchewan Type 72 dense graded asphalt mix comprised of siliceous aggregates. This research found that the addition of hydrated lime antistrip to the Saskatchewan Type 72 asphalt mix showed a considerable improvement in the mechanical behavior of the mix, including increased dynamic modulus, decreased strain, and increased phase angle. Although increased phase angle is generally not considered an improved material property in asphalt cement, an increase in phase angle in asphalt mixes may be an indication of improved strain dissipation by the asphalt binder due to more effective stress transfer from the aggregate to the asphalt matrix through improved asphalt-aggregate bonding. This improvement in laboratory mechanical behavior concurs with improved rutting and fatigue performance observed within typical Saskatchewan dense graded asphalt mixes when treated with lime antistrip.

Many government agencies are faced with the challenge of pavement evaluation and maintenance as part of their pavement management systems. These agencies perform or contract manual or automated distress surveys over the pavement network to monitor the structure performance and obtain the necessary data to calculate pavement condition indexes. Although manual distress ratings are done according to well-defined criteria, a certain amount of subjectivity and the experience of the raters have an undoubted influence on the ratings. This study proposes a new approach to estimate the interrater or intercrew reliability for manual or semiautomated distress data collection. The proposed analysis acknowledges that a certain degree of variability in the visual distress ratings is likely to occur and, thus, minimum acceptable values of complete and partial agreements of the crews or raters are suggested. The statistical approach to validate the level of agreement between the ratings of two raters or crews is based on the use of the chi-square distribution to test hypotheses about multinomial experiments.