Flexible drop-off and pick-up (one-way) carsharing programs provide users with high levels of convenience but meanwhile incurs spatiotemporal imbalances in shared-cars distribution. Predicting shared-car use helps recognize system imbalances beforehand while identifying determinants related to shared-car use helps operators efficiently implement relocation strategies. In this study, a gradient boosting regression model (GBRT) is employed to predict shared-car use at a station level, and partial dependence plots (PDPs) are employed to examine nonlinear relationships between shared-car use and various predictors. Results show: (1) GBRTs predict shared-car use with a high level of accuracy (MSE: 1.1069–1.1648). (2) PDPs present highly consistent results with relationships derived from the traditional statistical model; (3) Time-varying variables account for 89.30%–86.84% importance in shared-cars use prediction, suggesting these variables can greatly enhance prediction accuracy; (4) Other variables like built environment, station attributes, and socioeconomic features, also account for some importance and can enhance prediction accuracy. Findings help carsharing operators accurately predict the station-level shared-car use and optimally identify the best locations for stations, and thus maintain the operational efficiency of carsharing programs.

Global aging has raised increasing concerns on the health and well-being of older adults. Public transport is a viable option to improve the mobility and quality of life among older adults. However, policies that promote the public transport use among older adults are rare. This study utilizes the eXtreme Gradient Boosting (XGBoost) decision tree to explore the non-linear associations of the built and social environment with bus use among older adults in China. The bus use of older adults was obtained from the Zhongshan Household Travel Survey (ZHTS) in 2012. Results show that non-linear relationships exist among all built environment and social environment characteristics. Within certain thresholds, the percentage of green space land use, land use mixture, bus-stop density, and dwelling unit density are positively related to bus use among older adults. Likewise, one social environment variable, the proportion of older adults in a neighborhood, is the key social environment variable. Furthermore, the dwelling unit density and proportion of older adults appear to have an inverse U-shaped relationship. Additionally, age, ownership of motorcycles, and distance from home to the nearest bus stop also show non-linearity. The findings presented in this paper facilitate effective planning interventions to promote bus use among older adults.

Aim: Promoting walking activity is an effective way to improve the health of older adults. Walking frequency is a critical component of walking behavior and an essential determinant of daily walking levels. To decipher the association between the built environment and walking frequency among older adults, this study's aims are as follows: (1) to empirically test whether non-linear relationships between the two exist, and (2) to identify the thresholds of the built environment characteristics that promote walking.Methods: The walking frequency of old adults was derived from the Zhongshan Household Travel Survey (ZHTS) in 2012. The sample size of old adults aged 60 or over was 4784 from 274 urban and rural neighborhoods. A semi-parametric generalized additive model (GAMM) is used to analyze the non-linear or non-monotonic relationships between the built environment and the walking frequency among older adults.Results: We found that non-linear relationships exist among five out of the six built environment characteristics. Within certain thresholds, the population density, sidewalk density, bus stop density, land use mixture, and the percentage of green space are positively related to older adults' walking trips. Furthermore, the land use mixture and the percentage of green space show an inverse “V”-shaped relationship.Conclusions: Built environment features can either support or hinder the walking frequency among older adults. The findings in the current study contribute to effective land use and transport policies for promoting active travel among older adults.

Well-designed wayfinding signs play an important role in improving the service level of metro stations, ensuring the safety of passengers in evacuation, and promoting the sustainable development of public transport. This study explored the effects of ambient illumination, color combination, sign height, and observation angle on wayfinding signs’ legibility in metro stations. In the experiment, simulated metro-wayfinding signs were made to test legibility. As designed, the legibility was measured based on the following independent variables: two levels of ambient illumination (70 lux and 273 lux), two target/background color combinations (achromatic-white target on black background, chromatic-yellow target on black background), two sign heights (1.5 m and 2 m), and three observation angles (0°, 45°, 70°). The results showed that brighter ambient illumination provided passengers with higher legibility. Achromatic color combination was more legible than chromatic color combination, but not significantly. Different types of signs, set at different height, did not directly affect legibility. Observation angle had significant effects on legibility. Visibility catchment area of wayfinding signs was like an ellipse, with its short axis nearly equal to the legibility distance of the sign at 0 degrees. The findings will facilitate the layout and setting location of wayfinding signs in metro stations and improve the level of wayfinding service.