Minimizing energy consumption is a key issue from both an environmental and economic perspectives for railways systems; however, it is also important to reduce infrastructure construction costs. In the present work, an artificial neural network (ANN) was trained to estimate the energy consumption of a metropolitan railway line. This ANN was used to test hypothetical vertical alignments scenarios, proving that symmetric vertical sinusoid alignments (SVSA) can reduce energy consumption by up to 18.4% compared with a flat alignment. Finally, we analyzed the impact of SVSA application on infrastructure construction costs, considering different scenarios based on top–down excavation methods. When balancing reduction in energy consumption against infrastructure construction costs between SVSA and flat alignment, the extra construction costs due to SVSA have a return period of 25–300 years compared with a flat alignment, depending on the soil type and construction method used. Symmetric vertical sinusoid alignment layouts are thus suitable for scattered or soft soils, up to compacted intermediate geomaterials.

Transit-oriented shopping mall development (TOSMD) is a novel concept in urban planning practice. The array of TOSMD attractiveness factors is not currently included in the forecasting models for station ridership. As a result, a station near a TOSMD can reach its capacity because its design and development didn't take into account TOSMD, while TOSMD contributes passenger flow to the station. Depending on the setting, the number of visiting tourists could exacerbate this problem. Therefore, this study aims to empirically identify the critical TOSMD attractiveness factors and clarify their impact in terms of shopper passengers contributing to the ridership at stations near TOSMDs in the case of the Dubai Metro Redline. A sample of 700 shopper passengers were surveyed at seven stations near TOSMDs. We used principal component analysis with confirmatory factor analysis, and structural equation modelling to explain the impact of TOSMD attractiveness on shopper passenger ridership at stations near TOSMDs. Eleven independent TOSMD attractiveness factors were found to be associated with the extent of shopper passengers’ intention to use a station near a TOSMD. Resident and tourist shopper passengers showed variability in the factors impacting their use of stations near TOSMDs. The study assists in empirically validating the impact of TOSMD attractiveness on ridership at stations near TOSMDs, as a means of increasing the economic sustainability of transit networks. It provides statistically fit models for clarifying the generated resident and tourist shopper passenger ridership contributing to a station ridership as a result of its nearby TOSMDs. For a more comprehensive analysis, future studies could be repeated for transit networks in other cities.

The performance of employees in a transport set is highly affected by their satisfaction and occupational problems. Underground metro drivers work in special conditions as compared with the drivers of suburban trains and urban tramways. Even though several studies have focused on the ergonomics of train drivers, there is a dearth of research on underground metro drivers. This study was conducted to investigate the factors affecting the underground metro drivers’ occupational problems such as depression and level of satisfaction. The study was carried out on underground metro drivers in Tehran, Iran. The required data were collected through interviews, self-report tests and a depression scale. The classification and regression tree (CART) model was used to measure the relationship among depression, different conditions and other demographic characteristics. By using hierarchical clustering, metro drivers were divided into two categories with desirable and undesirable levels of satisfaction with regard to varying levels of satisfaction in different fields. By labelling them and reusing the CART model, the most important parameters affecting the satisfaction of drivers were extracted. The results indicated that more than half of metro drivers were depressed. The most important factors in the incidence of depression were: resentment of some psychological factors such as dissatisfaction with loneliness in the cabin, stress and fear of an incident, fatigue, dissatisfaction with the resting place, work experience more than 3.5 years, dissatisfaction with rights and the need for a second job. Also, the most important factor affecting satisfaction was the quality of the resting place.

In the original publication figures 4, 5, 6 have been removed due to not having the appropriate permissions to reproduce the images contained in the figures. Figure 8 has a problem of R2 mark. The revised figures are provided in this correction.