Walking, as a major mode of travel or activity among older adults, deserves more attention in research on travel behavior related to the neighborhood built environment. However, most previous research has examined global relationships or assumed that all spatial scales are identical rather than focusing on the intensity of spatial scale differences between explanatory variables and travel behavior. Therefore, this paper employs a multi-scale, geographically weighted regression model to analyze the effect of the neighborhood built environment on the walking activities of 863 older adults in Taiyuan, China, using survey data. The results indicate that the influence intensity of the explanatory variables is determined, in descending order, by the number of retail establishments, the number of pedestrian crossings, the number of restaurants, the residential density, the land use combination, the number of recreation facilities, and the location and the number of bus stops. Moreover, the spatial scales of the number of recreation and public service facilities are greater than those of the other explanatory variables. This research can contribute to a better understanding of the relationships between the built environment of a neighborhood and walking activities and provide case support for the sustainable development of age-friendly transportation services.

Generally, low-mobility individuals, those with less access to transportation options and who are often marginalized in the social environment, can be divided into three groups: older adults, low-income individuals, and individuals with disabilities. This article analyzes the transportation demands of low-mobility individuals in China using travel characteristics and accessibility of public transportation. A mixed survey procedure, including a large-scale investigation and a supplementary investigation was used. The findings show that (1) there are different results regarding the transportation demands of the three low-mobility groups; (2) as a single entity, low-mobility individuals have similar transportation demands, which are inferior to those of the general public; and (3) the transportation demands of low-mobility individuals in China are not identical to those obtained by other researchers. The above results indicate that the analysis of the transportation demands of low-mobility individuals should not only consider the transportation demands of distinct groups of low-mobility individuals but should also consider all of them as a single entity in comparison to the general public. Furthermore, planners in developing countries who make policies for the improvement of transportation conditions for low-mobility individuals should gain advanced experience from developed countries and take the particular conditions of their own country into account in order to meet the demands of low-mobility individuals.

In this study, we created a practical traffic assignment model for a multimodal transport system considering low-mobility groups with the aim of providing the foundation of transportation network design for low-mobility individuals. First, the route choice equilibrium for walking, non-vehicle, and private car modes is described using the logit function, which is formulated as a variational inequality problem considering different low-mobility groups. Then, the practicalities related to travel times at intersections, traffic barricades between different lanes, and fuel fees of private cars are integrated to design a generalized travel cost function. Last, the method of successive weight averages is used to solve the proposed model. The model and its solution are verified based on a real case study of the city of Wenling in China. The sensitivity of adjustment parameters related to travel costs are analyzed, the practicality of the proposed model is explored, and the results of traffic assignment for different low-mobility groups are discussed.

Travel equity has always been an important but difficult topic in urban traffic research, especially for different groups. Firstly, based on bus operation, this paper constructs the ride change network using the ArcGIS platform. Secondly, through network analysis and based on the transfer network, the time measurement model of bus stops and the time accessibility measurement model of the traffic zones are used to measure and analyze bus stops and traffic zones, respectively. Finally, combined with the global and local spatial autocorrelation model, the travel space allocation equilibrium of pilgrimage is quantified. This case study shows that the time accessibility index reflects the fairness of pilgrimage resource allocation well. According to the overall and local Moran’s I index, the spatial distribution of the configuration equilibrium of the traffic zone is obtained. This paper offers two contributions to the literature: an assessment of the travel fairness of pilgrimage and conclusions that fill the research gaps on the travel equity of vulnerable groups. In this paper, the spatial fairness of pilgrimage behavior is studied, which reflects the fairness and balance of the public transportation system for pilgrimage, as well as the travel fairness of pilgrimage in various regions. The presented knowledge can promote the fairness of residential travel and achieve social equity.

The purpose of this study is to create a bi-level programming model for the optimal bus stop spacing of a bus rapid transit (BRT) system, to ensure simultaneous coordination and consider the interests of bus companies and passengers. The top-level model attempts to optimize and determine optimal bus stop spacing to minimize the equivalent costs, including wait, in-vehicle, walk, and operator costs, while the bottom-level model reveals the relation between the locations of stops and spatial service coverage to attract an increasing number of passengers. A case study of Chengdu, by making use of a genetic algorithm, is presented to highlight the validity and practicability of the proposed model and analyze the sensitivity of the coverage coefficient, headway, and speed with different spacing between bus stops.