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Walking facilities are important infrastructures in communities. These facilities should be designed to accommodate the needs of all types of pedestrians. Unfortunately, existing design guidelines fail to offer adequate consideration for individuals with disabilities owing to a lack of empirical data. To address this knowledge gap, a controlled large-scale research project was conducted at Utah State University (USU) to study the walking behavior of people with various types of disabilities in various indoor walking facilities. These facilities included a passageway, different types of angles (right and oblique), bottleneck, and stairwells. The purpose of this paper is twofold: to examine the impacts of individuals with disabilities on crowd walking speed, and to study the impacts of different indoor walking facilities on the movements of various pedestrian groups. Results show that the presence of individuals with disabilities in a crowd significantly reduces the overall crowd speed. Statistical analysis also reveals similarities and differences between the walking speeds of various pedestrian groups. A regression model is calibrated to predict the speed of various types of individuals with disabilities in different indoor walking facilities. The findings of this paper may help urban planners and walking facility designers consider the needs of people with disabilities. [ABSTRACT FROM AUTHOR]

To advance public transportation development, it should be explored from the perspective of behavioral analysis. This paper adopts the theory of planned behavior (TPB) to study public transportation choice behaviors. The first aim is to explore the necessity of dividing subjective norms into an injunctive norm and a descriptive norm and to explore their roles in predicting behaviors. The second aim is to investigate the mechanism related to several key variables and their role in forming the intention to take transit. The third aim is to develop appropriate improvement strategies through the analysis of behavior, subjective norms, or perceived control beliefs. Empirical data were collected by distributing online and hard-copy questionnaires in Shanghai, China. A sample of 393 valid questionnaires was collected. An ordinal regression model was constructed based on the empirical data. The results reveal that TPB can be applied to explain choice behaviors with respect to public transport. Among the factors affecting travelers' intentions, attitude toward public transport is most decisive. Descriptive norms seem to have more direct effects on public transport use behaviors on the basis of the correlation coefficients. Injunctive norms, at least in this case, have a more obvious influence on travelers' intention to take public transport than do descriptive norms. Furthermore, on the basis of belief analysis, some critical approaches to improving the competitiveness of Shanghai public transportation are proposed that can be used to develop people-oriented public transportation policies and strategies in other similar cities. [ABSTRACT FROM AUTHOR]

Older adults, low-income individuals, and individuals with disabilities are generally considered 'low-mobility' individuals, having less access to transportation options and often marginalized in the social environment of the community. This study assessed the transportation needs of low-mobility individuals using three dimensions: (1) travel characteristics, (2) social strength in terms of transportation assistance received from their social networks, and (3) accessibility to public transportation. A mixed survey method combining an in-person interview at the collaborating organizations and a mail-back survey were used. Results showed that older adults remain mobile and make more frequent short trips. The results also showed a much higher reliance on private vehicles among older adults and individuals with low income, whereas a much higher reliance on public transportation and much lower reliance on private transportation was found among individuals with disabilities. Individuals with disabilities were still active, as almost half of them travel to work frequently. However, the number of nonwork trips made by individuals with disabilities was significantly low. These findings indicated a positive relationship between transportation mode choices and social dependence with family and friends. Individuals with stronger family social ties were more likely to receive adequate help meeting their transportation needs. The accessibility analysis revealed that low-mobility individuals in Cache County, Utah, have difficulties accessing transit due to the long walking distances from their residences. These findings may be used to guide policy for improving public transportation and paratransit services to meet low-mobility individuals' needs. [ABSTRACT FROM AUTHOR]

Combined travel demand models (CTDM) that integrate trip generation, trip distribution, modal split, and traffic assignment have been developed to resolve the inconsistency problem between the level-of-service and flow values of the sequential four-step travel demand forecasting procedure. In this paper, an improved partial linearization algorithm for solving the logit-based combined travel-destination-mode-route choice model formulated as a convex mathematical programming is developed. The improvements mainly focus on exploring recent advances in line search strategies to minimize the computational efforts required to determine a suitable stepsize that guarantees convergence. Specifically, the quadratic interpolation and the self-regulated averaging schemes are examined. Numerical results show that the self-regulated averaging line search scheme is more effective and efficient for solving the convex mathematical programming with a complex objective function in terms of solution quality and computational effort. [ABSTRACT FROM AUTHOR]

A procedure is developed to model network traffic for planning applications in small and/or medium-sized communities with limited planning resources. The proposed method is based on the theories and assumptions of conventional four-step travel demand models, but the baseline trip table is estimated from existing traffic counts using path flow estimator (PFE) to render a quick response approach that requires less data than the conventional approach. The proposed modeling approach is suitable for short-range, small area planning applications, such as the evaluation of alternative roadway networks that does not involve significant growth in trip generation patterns. A case study is set up with data from a small community (St. Helena, Calif.) to demonstrate the proposed approach. An O-D trip table is estimated with PFE from traffic counts. The estimation process is shown to be feasible as the results matched observed data with a satisfactory error bound. The traffic impacts of various scenarios of land use and network changes can be effectively evaluated with the proposed modeling approach. [ABSTRACT FROM AUTHOR]