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Addressing nautical bottlenecks is crucial for optimizing the utilization of inland waterways and maximizing the economic benefits of transports. To maximize economic benefits, a study was conducted to validate a key performance indicator (KPI)-based framework. This framework offers a structured approach to assessing the impact of resolved nautical bottlenecks on the economic benefits of inland waterway transport (IWT). To validate the applicability of the KPI framework, interviews with eleven experts were conducted. The goal was to prioritize each KPI based on their insights. The results of the interviews shed light on the relevance and coherence of both the individual KPIs and the overall KPI framework. The experts confirmed the importance of measures related to transportation efficiency, such as reduced transit times, increased vessel throughput, and enhanced reliability. The validated KPI-based framework serves as a valuable tool for policymakers, industry stakeholders, and researchers. It enables the assessment of the effects of resolving nautical bottlenecks in inland waterway systems. Future research should focus on quantifying the multifaceted impacts, making this framework even more useful for decision-making processes concerning investments in infrastructure upgrades and maintenance.

Transport can play a key role in mitigating climate change, through reducing traffic, emissions and dependency on private vehicles. Transport is also crucial to connect remote areas to central or urban areas. Yet, sustainable and flexible transport is among the greatest challenges for rural areas and rural–urban regions. Innovative transport concepts and approaches are urgently needed to foster sustainable and integrated regional development. This article addresses challenges of sustainability, accessibility, and connectivity through examining complementary systems to existing public transport, including demand-responsive transport and multimodal mobility. We draw upon case studies from the Metropolitan Area of Styria, Ljubljana Urban Region and rural Wales (GUSTmobil, REGIOtim, EURBAN, Bicikelj, Bwcabus, Grass Routes). In-depth analysis through a mixed-methods case study design captures the complexity behind these chosen examples, which form a basis for analysing the effects of services on accessibility for different groups, connectivity to public transport and usability as a “first and last mile” feeder. We further explore the weaknesses of complementary transport systems, including legal, organisational and financial barriers, and offer potential solutions to structure and communicate complementary transport systems to improve access and use. Looking ahead, we use the case studies to anticipate innovative, sustainable “mobility as a service” (MaaS) solutions within and between urban and rural areas and consider how future public policy orientations and arrangements can enable positive change. A main concern of our article and the contribution to scientific literature is through exploring the benefit of well-established multi-level governance arrangements when introducing smaller-scale mobility solutions to improve rural–urban accessibility. It becomes clear that not a one-size-fits-all model but placed-based and tailored approaches lead to successful and sustainable concepts.

Sustainable transport, such as using inland waterway transport (IWT), represents a major pillar of the European Green Deal to reduce global warming. To evaluate the different inland transport modes (road, rail, IWT), it is crucial to know the external costs of these modes. The goal of this paper is a critical review of external cost categories (e.g., accidents, noise, emissions) and external cost calculation methods of IWT to provide ideas for future research. We identified 13 relevant papers in a literature review dealing with external costs of IWT. In a meta-analysis, the papers were assigned to the seven external cost categories: accident, noise, congestion, habitat damage, air pollution, climate change and well-to-tank emissions. The most investigated external cost categories are climate change, air pollution and accidents. Two studies were identified as the major external cost calculation methods for IWT in the abstract. Our paper shows that the data basis of IWT is significantly lower than for road/rail. The measurement of energy consumption and related emissions of IWT needs to be qualitatively and quantitatively improved and brought up to the level of road traffic, to ensure an accurate comparison with other modes of transport.

Research shows that about half of all motorcycle collisions with other vehicles were caused by the accident opponent, typically a passenger car. This study aimed to assess the effect of simulator training on improving car drivers’ perceptibility of motorcycles and thereby addressing this frequent type of motorcycle accident from the perspective of the initiator. For this purpose, a training program with different methods was conducted and tested in a driving simulator with 80 learner drivers aged between 15 and 27 years, assigned to a control group and three training groups: variable priority, equal priority, and equal priority with warning. The conflict scenarios were determined based on an analysis of motorcycle–car accidents. The variable priority training program resulted in better perceptibility of motorcycles as compared to the equal priority training program and equal priority with warning in two out of four test setups, i.e., urban roads with high contrast between motorcycle and the driving environment and on rural roads with a low contrast. Most participants rated each training method in the driving simulator as useful and would recommend it to other learner drivers. These results are important because they show that simulator training has a positive effect on the motorcycle detection performance of learner drivers. The early perception of motorcycles in car drivers is essential for preventing collisions between cars and motorcycles.

The increasing use of electric vehicles, combined with the trend of higher charging currents, puts a significant strain on the electrical grid. Many solutions to this problem are being discussed, some relying on some form of smart grid, others proposing stricter regulations concerning charging electric vehicles. In this study, a different approach, called randomly delayed charging, is explored. The main idea is to charge a battery over night, but instead of starting the charging process as soon as possible, introduce a random delay, satisfying the boundary condition that the battery is sufficiently charged in the morning. Benefits of this technique are investigated by using an agent-based simulation that simulates commuters and calculates the electricity demand with temporal resolution. Results suggest that randomly delayed charging can have a significant effect on peak load caused by charging and that this benefit increases the higher the used charging current is. Randomly delayed charging can be a viable option for reducing the peak electricity demand that is caused by charging electric vehicles.

Forest fires are becoming a serious concern in Central European countries such as Austria (AT) and the Czech Republic (CZ). Mapping fire ignition probabilities across countries can be a useful tool for fire risk mitigation. This study was conducted to: (i) evaluate the contribution of the variables obtained from open-source datasets (i.e., MODIS, OpenStreetMap, and WorldClim) for modeling fire ignition probability at the country level; and (ii) investigate how well the Random Forest (RF) method performs from one country to another. The importance of the predictors was evaluated using the Gini impurity method, and RF was evaluated using the ROC-AUC and confusion matrix. The most important variables were the topographic wetness index in the AT model and slope in the CZ model. The AUC values in the validation sets were 0.848 (AT model) and 0.717 (CZ model). When the respective models were applied to the entire dataset, they achieved 82.5% (AT model) and 66.4% (CZ model) accuracy. Cross-comparison revealed that the CZ model may be successfully applied to the AT dataset (AUC = 0.808, Acc = 82.5%), while the AT model showed poor explanatory power when applied to the CZ dataset (AUC = 0.582, Acc = 13.6%). Our study provides insights into the effect of the accuracy and completeness of open-source data on the reliability of national-level forest fire probability assessment.

The urban population has been growing rapidly, especially in the European Union. The trend of urbanization has led to an increased demand for mobility, through both passenger and goods transportation. One of latest trends in passenger transportation is electric scooters, which have been offered under a framework of shared mobility since 2017. This paper addresses an optimization problem emerging from the process of collecting e-scooters from the streets of Vienna during the night. One of the major planning issues for rental companies is the uncertainty of service times, i.e., the time needed to locate and load the e-scooters onto the vans. We formulated the e-scooter collection problem as an extension of the vehicle routing problem with the goal of minimizing the number of vans needed to collect the scooters and the distance traveled by vans, as well as penalizing belated collection. We proposed a solution method based on a large neighborhood search and solved problem instances generated based on real-world data. We then evaluated the impact of the service time uncertainty on the total system costs through a scenario analysis. Furthermore, we proposed a dynamic re-optimization policy that made use of real-time information on service times. We showed that the dynamic policy outperformed the static policy by 4–17% and could lead to reductions in delays of 49–54%, depending on the standard deviation.

The rapid development of automated buses holds great potential for the development of transportation systems. As research into innovative forms of automated transportation systems gains momentum, it is important to understand the public’s perceptions of such public transport systems. Previous studies have contributed based on hypothetical scenarios, but not based on real observations. Based on an online survey in Stockholm in March 2019, the current research addresses this gap by investigating the public’s perceptions from a real, fully operational, automated public transportation service operated in a mixed traffic environment on public roads. The respondents were selected along the automated bus line in Barkabystaden, Stockholm. Our findings indicate that (1) The presence of onboard operators has a positive impact on respondents’ perceived safety, (2) People who have not taken automated buses before have a more negative perception of driving speed of the bus service than people who have taken the buses before, (3) Attitudinal factors, such as public perceptions of safety, driving speed, reliability, and convenience, have a significant influence on the acceptance of the new bus system, (4) As an emerging and innovative transportation mode, automated buses are expected to attract a high share of regular public transportation mode users and the younger generations in the future, (5) Social-demographic characteristics such as gender and income had no significant impacts on the adoption of the new technology. The results provide the characteristics of early bus adopters and their travel behavior and help to prioritize possible investments and allow the policymakers and private industries to identify the special needs of users.