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.

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.

Effective travel demand management measures provide the opportunity to fully utilize limited transportation resources, especially in underdeveloped areas. It is increasingly recognized that the improvement in existing transportation infrastructure and the optimization of traffic demand management method would result in a complicated urban transportation system with multiple travel modes. This paper aims to investigate the relationship between transportation improvements (e.g., pedestrian flow, free bus for the elderly, and parking space planning) and the mode choice behavior of pilgrimages in the Lhasa of Tibet, China. This study employed a distinctive survey conducted among pilgrims in Lhasa, including both individual questionnaires and interviews from 2010 to 2016. The analysis was undertaken using a multinomial logit model to identify the extent to which transportation improvements could affect the pilgrim’s travel mode choice behavior. The results show that transportation improvements, as an operational method in underdeveloped areas, play an important role in motivating the pilgrimage to travel that can increase the attractiveness of private car use, and make pedestrian traffic more prominent. However, improvements in the public transport need to be conducted to attract more travelers. These results confirm that increasing the attractiveness of low-carbon transportation (e.g., buses, walking, and cycling) to the public can reduce the usage on private vehicles and maintain the development of sustainable transportation in underdeveloped areas with limited transportation resources.

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.

In small, underdeveloped Chinese cities, residents have few options for transportation and travel service problems have not received enough attention from the authorities. This study examines residents’ preferred mode of travel in Lhasa and Yushu, China, two small and underdeveloped cities in which travelers tend to be economically disadvantaged. Travel data from different regions was analyzed to explore their commonalities. A structural equation model with latent variables is proposed to capture the heterogeneity not observed in the selection process. Results indicate that four of the six latent variables—preference for comfort, preference for reliability, preference for convenience and safety consciousness—are more helpful than preferences for flexibility and environmental awareness in explaining transportation utility, which could reflect residents’ travel behavior. Based on the results, respondents were divided into five groups with similar travel preferences through the k-means clustering method. The findings show that ensuring high comfort and convenience and moderate safety and reliability is conducive to increasing residents’ use of public transport. Furthermore, an examination of residents’ sociodemographic differences reflects that, in the future, active transport demand management should focus on trying to satisfy the preferences of female, low-income and elderly travelers.