Vienna’s geostrategic importance fluctuated through the ages because of the power clashes and subsequent political and socio-economic impacts on the population. This paper assesses its current position in a historical context and then focuses more on the socio-economic dimensions such as interconnectedness and other transport aspects of the geostrategic position. Air and environmentally friendlier modes of passenger transport like high-speed rail are considered and analysed in the European context. This paper also reviews the results and issues dealing with the development of the Vienna Airport and the progress of high-speed railway projects in the Central European Economies (CEEs) after the European Union’s enlargement in 2004. The results suggest that after a restoration period of Vienna’s geostrategic position between 1995–2005, there is currently only a moderate and slowly growing exercise of power, control or influence over the CEEs. The results suggest that there is competition from busier German hub airports as well as the growing importance of CEE airports in transit and growing passenger transport performance figures. The lack of environmentally friendly high-speed infrastructure as a viable option instead of the fastest air travel is preventing Vienna to strengthen its strategic position. Its strategic importance is highly affected by the underdeveloped transport networks in CEEs and the future development of the Vienna Airport as a major transport hub.

To better utilise the service capacity of the limited facilities of a metro station, as well as ensure safety and transport efficiency during peak hours, a large passenger flow control plan is studied through theoretical analysis and numerical simulation. Firstly, by passenger data collection and data analysis, the characteristics of the inbound and outbound passenger flow of a T metro station are analysed. Secondly, AnyLogic evacuation simulation models for the T Station during peak hours, peak hours without/with passenger flow control are established based on real passenger flow data as well as the station structures and layouts by using the AnyLogic software. The results show that there are no obvious congestions in the station hall, and the travel delay is significantly reduced when effective passenger flow control measures are taken. By controlling the speed, direction and movement path of passengers, as well as adjusting the operation of escalators, entrances and automatic ticket-checking machines, passenger flow can become more orderly, transport efficiency can also be improved, and congestion in the station can be well mitigated.

This paper proposes a functional carriage design and an evaluation index system to improve the operational efficiency of high-speed medical trains. Hierarchical task analysis and human-machine-environment analysis were applied to model the transfer task and the functional modules of the medical train. The functional module configuration was obtained by performing a correlation analysis between the task and function. The relationship between carriages was elucidated by analysing material, personnel and information flow, and an optimal grouping diagram was obtained. Based on this design method, an innovative 6-carriage grouping design scheme was proposed. A functional evaluation index system for the carriage design was constructed, and the 6-carriage design was compared with the conventional 8-carriage design to verify the usability of the design method. The results showed that the 6-carriage high-speed trains can be flexibly configured to suit the changing task environment and are generally better than the 8-carriage design. This study provides theoretical and methodological support for constructing efficient and rational functional carriages for high-speed medical trains.

The paper concerns the method of determining the probability of unproductive manipulations during operations, maintenance or repairs on an inland intermodal terminal. The method is mathematically based on the semi-Markov process. The developed method enables revision of unproductive manipulation frequency and duration. It provides an opportunity to analyse and change inland terminal operations so as to increase productivity.

Tourism traffic has a considerable influence on the state of urban traffic in tourist cities. To consider tourism traffic demand in the division of conventional traffic analysis zones (TAZ), a spatial analysis method combining dynamic traffic state features with static land use and road network characteristics is proposed to define tourism traffic analysis zones (TTAZs). Taking Xiamen Island as an example, first, point of interest (POI) data for the tourism elements on Xiamen Island and kernel density estimation (KDE) are applied to determine the core zones impacted by tourism traffic. Second, within the impacted zones, this paper studies the dynamic distribution of the tourism traffic for peak hours during holidays and non-tourism period by employing spatial autocorrelation method based on floating car data (FCD) and determines the area of slow traffic agglomeration of tourism traffic. In view of the distribution of tourism infrastructure, land use, tourism traffic state distribution and road network, this study identified the characteristics of slow traffic agglomeration in the area near Siming Road and divided four TAZs into six TTAZs. By further dividing the urban TTAZs, this paper hopes to provide a reference for urban traffic planning and management, tourism planning and land use planning.

This paper focuses on the potential safety hazards of collision in car-following behaviour generated by deep learning models. Based on an intelligent LSTM model, combined with a Gipps model of safe collision avoidance, a new, Gipps-LSTM model is constructed, which can not only learn the intelligent behaviour of people but also ensure the safety of vehicles. The idea of the Gipps-LSTM model combination is as follows: the concept of a potential collision point (PCP) is introduced, and the LSTM model or Gipps model is controlled and started through a risk judgment algorithm. Dataset 1 and dataset 2 are used to train and simulate the LSTM model and Gipps-LSTM model. The simulation results show that the Gipps-LSTM can solve the problem of partial trajectory collision in the LSTM model simulation. Moreover, the risk level of all trajectories is lower than that of the LSTM model. The safety and stability of the model are verified by multi-vehicle loop simulation and multi-vehicle linear simulation. Compared with the LSTM model, the safety of the Gipps-LSTM model is improved by 42.02%, and the convergence time is reduced by 25 seconds.

The crossing decisions and behaviour of elderly pedestrians are affected by the pedestrian level of service (PLOS). In this paper, an evaluation model was established to analyse the relationship between the traffic environment and the perceived evaluation of elderly pedestrians. Firstly, the characteristic parameters of the selected intersections and the perceived evaluation data of elderly pedestrians at the synchronisation scenery were extracted using manual recording and questionnaire-based truncation methods. The correlation between the perceived evaluation data of elderly pedestrians and the traffic parameters were tested with respect to the dimensions of safety, convenience and efficiency. Then, the significant parameters affecting PLOS were recognised. Based on the traffic characteristic parameters, the PLOS evaluation model from the elderly perspective was established using the fuzzy linear regression method. PLOS classification thresholds were obtained using the fuzzy C-means clustering algorithm. The data from two intersections were used to validate the model. The results show that the difference between the actual and the predicted PLOS values of the two crosswalks were 0.2 and 0.1, respectively. Thus, the proposed PLOS evaluation model in this paper can be used to accurately predict the PLOS from the elderly perspective using the traffic data of signalised intersections.

Connected automated vehicles (CAV) can increase traffic efficiency, which is considered a critical factor in saving energy and reducing emissions in traffic congestion. In this paper, systematic traffic simulations are conducted for three car-following modes, including intelligent driver model (IDM), adaptive cruise control (ACC), and cooperative ACC (CACC), in congestions caused by rear-end collisions. From the perspectives of lane density, vehicle trajectory and vehicle speed, the fuel consumption of vehicles under the three car-following modes are compared and analysed, respectively. Based on the vehicle driving and accident environment parameters, an XGBoost algorithm-based fuel consumption prediction framework is proposed for traffic congestions caused by rear-end collisions. The results show that compared with IDM and ACC modes, the vehicles in CACC car-following mode have the ideal performance in terms of total fuel consumption; besides, the traffic flow in CACC mode is more stable, and the speed fluctuation is relatively tiny in different accident impact regions, which meets the driving desires of drivers.

Cities, even medium-sized and small ones, have become overwhelmed by traffic and congestion. Innovative solutions are required and recent studies have focused on sustainable approaches. This study aims to develop a multimodal transport model consisting of an urban public transportation (UPT) service combined with an e-scooter sharing service. The main purpose of the model is a comparison between two travel alternatives (car and UPT + e-scooter), calculating their associated levels of utility. The methodology is based on a multinomial logit model, implemented in Matlab software, using results from an online mobility survey (socio-economic characteristics of potential users of e-scooters). The additional aim is related to the assessment of the inhabitants’ availability to shift from car to multimodal service or to simple e-scooter service. The developed micromodel was applied in Iași, a mid-sized city located in the northeast of Romania. Several price strategies were analysed in order to find their influence on users’ mobility behaviour. It turned out that the price for the shared e-scooter is too high at this moment to be used for daily travel. Without a price decrease and public authorities’ involvement in facilitating the multimodality, the e-scooter remains only an entertainment activity.

Current analytical free-flow speed models consider all rural two-lane highways as the same road type despite their different functional significance in the network. The aim of this paper is to develop a prediction model for free-flow speed as a function of speed limit and road geometric characteristics for different classes of rural two-lane highways. The research was conducted on 50 representative sections of the two rural classes of two-lane highways equipped with automatic traffic counters in Serbia. In order to develop the appropriate models, it was necessary to determine the threshold values of vehicle time headway in the free-flow for both classes of rural two-lane highways, based on the total number of 191,720 vehicles. The obtained results show that there are differences in the threshold values of free-flow time headway for different road classes. Namely, it was determined that the values of free-flow time headway for Class I amounted to 6.3 s, and for Class II to 8.4 s. The free-flow speed prediction model for different road classes showed that speed limit had the highest impact on free-flow speed for Class I and II highways, followed by horizontal curve radius and shoulder width.

Transport is an industry that generates a significant portion of national income and directly or indirectly employs a large number of workers, while supporting the existence and development of all other sectors of the economy. Despite the long-standing goal of decoupling economic and transport growth in the European Union (EU), freight transport volumes, especially road freight transport, continue to increase. This leads to a deterioration of the quality of life and the environment, but on the other hand also creates business opportunities. The question is which country’s haulers will benefit the most. Using a shift-share analysis, the authors provide an overview of the dynamics of the EU road freight market and select countries for closer examination. They then examine the extent to which the road freight sector contributes to national income in these countries. Using a regression analysis, they estimate transport prices and changes in turnover and gross value added (GVA) for selected countries due to market structure change. The results show that the sector’s turnover increased by 4% due to market changes, sectoral GVA deviated only slightly, and there was a loss of at least 8 billion EUR in GVA due to the shortage of truck drivers.

The expansion of logistics requirements, limited space and strict requirements of generators of logistics requests (GLR) in terms of service quality complicate the supply of the region, resulting in the necessity to improve logistics models (MoL). Proximity to water, the presence of ports and piers along the coast, new eco vehicles and the development of cooperation between land and water transport are elements for improving the existing MoLs in an economically and environmentally acceptable way. Research on the development of an improved multi-echelon logistics network with variable terminals including the coordination and cooperation of a heterogeneous group of transport agencies for the realisation of goods flows represents an innovation in regional logistics (RL). This article presents an integrated MoL development process using dynamic optimisation with a focus on spatial, temporal, transport, economic and environmental components.