Rail transportation planning is a continuous, multi-phase, functioning scale that is based on reconstructing the spatial system, thus contributing to build a more quality-focused, long-term-oriented and balanced approach. This paper presents cartographic modelling and multi-criteria analysis (CMCA) for the optimum route/station location in accordance with selected criteria and constraints for rail transit system planning. The methodology is based on overlay analysis (cartographic modelling) to combine diverse criteria maps and the analytic hierarchy process (AHP) method for criteria weighting. The purpose of the study is to examine a GIS multiple-criteria decision-making (MCDM) framework by considering Stream, Geology, Slope, Land use and Population decision criteria. The decision modelling framework conceives an additional prominent approach by co-producing with the public, especially for underserved areas of low socio-economic status and public user expectations in the railway transport planning process. This model applied to a candidate metro line referred to as M 18 (Başakşehir-Esenyurt-Beylikdüzü) with eight railway stations for the preliminary stage evaluation. The outcomes of this research will close the gap by establishing a novel suitability framework which can be used as a preliminary analysis for transforming and developing urban rail transit networks.

The suspension-type monorail (STM) is a new type of rail transit, currently developing rapidly in China. Due to its short construction duration and high terrain adaptability, STM can save large land resources. In particular, by supplementing the traffic systems in large and medium-sized cities, STM can contribute to green tourism projects. However, no systematic study is devoted to the STM transit system in China, and there is still a lack of relevant knowledge and exploration, especially for the special combination system monorail bridge. In view of the real STM bridge, namely a long-span (55 + 100 + 55)-m cable-stayed bridge in this paper, and by applying wind-vehicle-bridge coupling vibration theory, ANSYS finite element method software, and Universal Mechanism multi-body dynamics software, finite element models are established for the bridge and multi-body vehicle, respectively. Furthermore, a co-simulation method is adopted to analyze vehicle-bridge coupling vibrations and ride comfort quality. According to the results, the dynamic responses of the monorail bridge and vehicle are greatly affected by the variation in wind speed, and it is necessary to take measures to decrease system vibrations, thereby ensuring ride comfort quality for vehicle passengers.

This study aims to analyse the inter-rail modal shift behaviour of suburban rail passengers to examine ridership for the proposed metro extension corridor in Chennai, India. This investigation was conducted in 2019 as part of a feasibility study for the extension of the metro line spanning between Chennai Airport and Kilambakkam, a southern suburb of Chennai. The same origin–destination pair is also served by the suburban rail system. It is an extension of the operating line from Washermenpet to the airport of the Phase I metro project. For this inter-rail competition study, a sample of 272 suburban rail passengers covering work, education and other trip purposes were interviewed using a stated preference questionnaire. Six stated scenarios were considered for analyses which included travel time saving by using the metro along with the fare difference between metro and bus. The study revealed that suburban rail passengers were less concerned about travel time saving and gave priority to fare difference irrespective of trip purpose. This shows the unique metro choice behaviour of suburban rail travellers in the Indian context.

Transit-oriented development (TOD) has been promoted worldwide as an integrated land-use and transportation strategy to foster urban sustainability. Bike share provides people with a convenient and relatively affordable way to enlarge the spatial scale of TODs across urban communities, as a solution to the first/last mile (FLM) issue with respect to the transit nodes of TODs. Even though barriers to FLM have been frequently studied, few studies incorporate people’s perceptions of their barriers and/or the integration of multiuse paths (MUPs) into the network of bike share and public transit. Using a survey conducted in the Greater Cincinnati area, Ohio, this study aimed to answer the following questions: (1) What are people's major barriers to integrating different green transportation modes and/or facilities (bike share, MUPs, public transit)? (2) To what extent does the built environment around people’s residential location affect their integration level of MUPs, bike share, and public transit? (3) Which improvements would most likely encourage people to integrate them more often? With descriptive statistics, spatial analysis, and statistical comparison, we found that (1) the major barrier to integrating MUPs into the green transportation system was their lack of connection and availability to transit and bike share; (2) a person’s living environment is spatially related to whether a person integrates bike share; and (3) more respondents would use MUPs more often if an integrated green transportation system could be provided or improved. These findings suggest the potential of incorporating MUPs and bike share into TOD strategies to address the FLM issue.

The imbalance between the supply and demand of shared bikes is prominent in many urban rail transit stations, which urgently requires an efficient vehicle deployment strategy. In this paper, we propose an integrated model to optimize the deployment of shared bikes around urban rail transit stations, incorporating a seasonal autoregressive integrated moving average with long short-term memory (SARIMA-LSTM) hybrid model that is used to predict the heterogeneous demand for shared bikes in space and time. The shared bike deployment strategy was formulated based on the actual deployment process and under the principle of cost minimization involving labor and transportation. The model is applied using the big data of shared bikes in Xicheng District, Beijing. Results show that the SARIMA-LSTM hybrid model has great advantages in predicting the demand for shared bikes. The proposed allocation strategy provides a new way to solve the imbalance challenge between the supply and demand of shared bikes and contributes to the development of a sustainable transportation system.