Aging has long been recognized as a major distress mechanism for asphalt concrete and, by extension, asphalt pavements. Aging causes the material to stiffen and embrittle, which leads to a high potential for cracking. Although a significant amount of effort has been placed on understanding the aging process of asphalt binder, less effort has been put forth to develop laboratory aging procedures for producing aged mixture specimens for performance testing. An optimal laboratory conditioning procedure to simulate long-term aging for performance testing and prediction is required in order to integrate the effects of long-term aging in pavement prediction models and other mechanistic design and analysis methods. In this study, oven aging and pressure aging vessel aging are applied to both loose mix and compacted specimens in order to evaluate and select an aging method to simulate long-term aging for performance testing and prediction. The selected method must be able to maintain specimen integrity in order to be used for performance testing and prediction. Efficiency, practicality, and versatility also are considered in evaluating the aging methods. The results demonstrate that loose mix aging in an oven is the most promising aging method to produce mixture specimens for performance testing in terms of efficiency, specimen integrity, versatility, and cost.
Aging of asphalt mixtures occurs during production and construction and continues throughout the service life of the pavement. Although this topic has been studied extensively, recent changes in asphalt mixture components, production parameters, and plant design have raised a need for a comprehensive evaluation that considers the impacts of climate, aggregate type, recycled materials, WMA technology, plant type, and production temperature. In this study, field cores were acquired from seven field projects at construction and several months afterwards, and raw materials were also collected for fabricating laboratory specimens that were long-term oven aged (LTOA) in accordance with selected protocols. The resilient modulus and Hamburg wheel tracking tests were conducted on both specimen types to evaluate the evolution of mixture stiffness and rutting resistance with aging. The concepts of cumulative degree-days and mixture property ratio were proposed to quantify field aging and its effect on mixture properties. Test results indicated that the LTOA protocols of two weeks at 140°F (60°C) and five days at 185°F (85°C) produced mixtures with equivalent in-service field aging of 7–12 months and 12–23 months, respectively, depending on climate. Finally, among the factors investigated in the study, WMA technology, recycled materials, and aggregate absorption exhibited a significant effect on the long-term aging characteristics of asphalt mixtures, while production temperature and plant type had no effect.
Bus Rapid Transit (BRT) has generated great interest among small and large cities across the United States (e.g., Detroit, MI, Grand Rapids, MI, and Aspen, CO) as a means of improving mobility and accessibility, and optimizing the use of street space, at a relatively modest cost per mile ($10-$27 million). The main advantage of BRT is its ability to operate on all types of road infrastructures: mixed-flow arterials, mixed-flow freeways, dedicated arterial lanes, at-grade or fully grade-separated transitways, managed lanes, and tunnels. The purpose of this study is to identify BRT-advantaged age-groups and income level groups by examining various BRT cities. A group or sector is said to be “BRT-advantaged” when its population grows at a higher rate within a BRT shed than within the larger metropolitan region during the same time period. Shift-share analysis was conducted to identify various BRT-advantaged attributes. Shiftshare analysis is used to decompose changes in an attributes (such as age-group and income level) in local areas. For example, the analysis identifies age groups that have comparative advantage in local areas. The technique provides a picture of how well a region’s income level group and age groups are growing at a given moment in time. As a part of this effort, age-group and income level data of five BRT cities were collected before and after the implementation of BRT at region and BRT-shed level. BRT-advantaged attributes by each city, as well as combined were identified. With the precedent of specific populations thriving in a BRT shed, communities and their planners can target the appropriate age and income level groups in their marketing efforts. The author discussed the causes behind the influence of BRT on the various population groups.
This paper describes the outcome of an exploratory step in the lead author’s broader research agenda funded through a Discovery Grant by the Natural Sciences and Engineering Research Council of Canada (NSERC) called “Developing planning and forecasting tools for age-friendly rural and community transportation alternatives: a focus on volunteer driver programs to facilitate older person mobility and safety”. It incorporates the results of an undergraduate special study that involved working with seven different regional volunteer driver programs in New Brunswick to catalogue the type and extent of trip and contextual information that they collect. The goal was to identify opportunities for consistent reporting practices that could enhance day-to-operations, as well as contribute to long term and strategic transportation planning incorporating these programs.
A bicycle-sharing system (BSS) is intended to provide increased convenience to individuals because they can use the service without the costs and responsibilities associated with owning a bicycle for short trips within the service area of the system. These systems are recognized to have traffic and health benefits such as flexible mobility, physical activity, and support for multimodal transport connections (Shaheen et al., 2010). Given the recent rapid growth of bicycle-sharing systems as a viable and sustainable mode of transportation for short trips, there is substantial interest in identifying contributing factors that encourage individuals to use these systems. This paper looks at BSS behavior at a trip level to analyze bicyclists’ destination preferences using a random utility maximization approach. Understanding the individuals’ decision processes in adoption and usage of bicycle-sharing systems will enable bicycle-sharing system operators/analysts to enhance their service offerings. Specifically, we study the decision process involved in identifying destination locations after picking up the bicycle at a BSS station. There have been several location choice studies in traditional travel demand literature that adopt a random utility maximization approach for understanding destination/location preferences (Chakour and Eluru 2014 Waddell et al. 2007; Sivakumar and Bhat, 2007). In this paper, we adapt this approach to the bicycle-sharing system data.
The aim of this paper is to investigate the impact of stated adaptation and opinion responses on individuals’ mode choice before and after travel demand management (TDM) strategy implementation. This investigation makes use of econometric modelling approaches, including the scaled multinomial logit model to capture these trends. This approach allows for the interpretation of differences in the decision making process based on the parameterization of the scale. The key outcomes of this analysis provide new insights into the effectiveness of TDM policies drawn from the perceptions and attitudes of travelers. These insights will permit policy/decision makers to justify the allocation of resources to different policies based on small scale, easy to implement stated adaption surveys.