Due to the impacts of highway congestion, truck driver shortage, the need for energy security, and the increasing revenue gaps to finance highway infrastructure construction and renewal, there is a critical need to explore the opportunities and barriers to rail-truck multimodal transportation paradigms. This study proposes a two-step modeling approach to explore truck freight carrier perspectives on the factors that foster/impede their willingness to collaborate with rail freight carriers through multimodal freight collaboration, and how these factors are correlated with their operational and behavioral characteristics. Understanding these correlations can provide rail freight carrier decision makers insights for the design of targeted mechanisms that will be required for such collaborations to come to fruition, including: (1) adjusting the rail carrier operations; (2) adopting technology that is synergistic with those of truck freight carriers; (3) designs for uncontainerized cargo; and (4) improved quality control strategies for service.

This study investigates the influence of different surface characteristics on tire–road noise of thin-layer road surfacings by a statistical modeling method. The surface characteristics considered are surface texture and sound absorption. Correlation analysis and multivariate linear regression are performed to detect the combined effect of surface texture and sound absorption on tire–road noise levels. The texture is characterized by mean profile depth as well as texture level on an octave band of wavelengths, while the sound absorption is described by the absorption coefficients on the frequency spectrum as well as by the maximum absorption coefficient only. In the regression, principal component regression is used to reduce the multicollinearity between the explanatory variables. The influence of surface characteristics of thin layer surfacing on tire–road noise is observed from the regression results and the correlation analysis.

Prior research has focused on estimating the heath, air quality, safety, and congestion relief benefits of bicycling facilities. Bicycling facilities also provide bicyclists with a more enjoyable and safer feeling experience. An estimate of the total welfare change, or net benefits, associated with providing improved bicycle facilities should therefore include the value of these additional benefits. This study estimates welfare change as willingness to pay (WTP) for improvements in bicycling facilities using several different methods to value travel time. Three types of improvements are considered: cycle tracks, bicycle lanes, and street lighting. A stated preference survey asked respondents to choose between different levels of bicycle facility improvements and travel time, and also asked respondents for their average and marginal wage rates. Cycle tracks were valued the most, followed by street lighting and bicycle lanes. Greater cycling experience was associated with lower WPT, although increasing age was associated with higher WTP. WTP estimated from either average or marginal wage rates produced similar results, whereas the regional wage rate produced much higher WTP estimates.

The application of sustainable performance measures continues to increase with the development of sustainable rating systems such as leadership in energy and environmental design (LEED), as well as transportation-focused programs, such as Greenroads. Established transportation rating systems focus primarily on the design and construction of motorized facilities such as local roadways and highways. As a result, there is the opportunity to develop a rating system focused on shared-use paths that are for nonmotorized (pedestrian and cycling) mobility. The primary objective of this research is to develop a sustainable rating system for the design and construction of shared-use paths, called GreenPaths, in order to promote environmental, social, and economic benefits through the development process. Sustainable indicators (credits) for shared-use paths are developed and then weighted using the analytic hierarchy process. GreenPaths is then applied to a real-world shared-use path facility, the Buffalo Valley Rail Trail in Union County, Pennsylvania. The case study results indicate the applicability, relevance, and significance of the rating system toward measuring sustainable design and construction practices for shared-use facilities.

This paper presents a vehicle-type-specific headway distribution analysis in a freeway work zone. The goal of this paper is to provide a vehicle-type-specific model with different time periods using empirical work-zone data from highway I-91 in Greenfield, MA. A nonparametric approach with a Gaussian kernel is used to describe the vehicle-type-specific headway distribution in a freeway work zone. No assumption is required on how the headways should be distributed for nonparametric methods. The vehicles are classified into Car, Van, and Truck based on a FHWA vehicle-type classification scheme. Statistical tests indicate nonparametric distribution with Gaussian kernel outperforms the lognormal distribution in statistical sense according to the ${\chi }^2$ values. Further, another work zone dataset from Jacksonville, FL is utilized to examine the mixed headway scenario without specifying vehicle types. The $K-S$ and Chi-square test results suggest the necessity of considering the vehicle types separately. Following the results, a discussion regarding why nonparametric model is better and the future research directions are presented.