Search Results (1,830)

Smart cities are increasingly dependent on interconnected transportation systems; however, this connectivity exposes smart mobility networks to significant cybersecurity risks. Traditional Intrusion Detection Systems are ill-equipped for this environment, as they are designed for isolated systems or fixed network boundaries. Thus, they struggle to secure the complex and heterogeneous smart mobility networks, where various protocols and resource-constrained edge devices require more adaptive solutions. To address this limitation, we propose a novel hybrid deep learning framework that combines convolutional neural networks for spatial feature extraction, long short-term memory networks for temporal pattern recognition, and an attention mechanism for adaptive feature weighting, together forming a context-aware Intrusion Detection System. Our approach is evaluated across six benchmark datasets spanning vehicular networks, IoT ecosystems, cloud computing, and 5G environments—VeReMi Extension, CICIoV2024, Edge-IIoTset, UNSW-NB15, Car Hacking, and 5G-NIDD—a deliberately diverse selection that represents the heterogeneous nature of real-world smart mobility networks. Empirical evaluation using three different random seeds reveals the proposed framework achieves detection accuracy exceeding 98% on each dataset, a mean F1 score of 98.94%, and an inference latency of just 4.96 ms per sample. Our results show that the proposed model achieves consistently high detection performance across six heterogeneous benchmark datasets, making it a potentially robust candidate for real-time intrusion detection in smart mobility systems. Full article

Congestion in urban transportation is a significant challenge, often exacerbated by increasing private vehicle use and limitations in public transport. This study introduces a two-stage approach combining multi-criteria assessment and traffic simulation to examine current conditions and propose improvements. Initially, data on five primary and twenty-one secondary factors affecting public transport choice are assessed using the Best–Worst Method (BWM). The findings reveal that convenience is prioritized by working professionals, while travel cost is most important to students. A baseline simulation model is established using a case study at Kaset Intersection in Bangkok. Incorporating weighted preferences into the simulation aims to enhance public transport and encourage private car users to switch modes through potential traffic management policies. Additionally, a micro-simulation assesses the impacts of decreased traffic density, revealing that a reduction in traffic density can shorten overall travel time by about 2.04 s, based on regression analysis. The results suggest policies to improve public transport, reduce traffic density, and enhance urban transport system performance. Full article

Mathematical modeling plays a key role in understanding and optimizing transport system operations under uncertain and dynamic conditions. This study proposes a data-driven predictive framework for estimating passenger-accepted vehicle occupancy, addressing a critical gap in transport system planning under public health-related constraints. Using data from a structured survey conducted across seven Southeast European countries (N = 476), the study integrates statistical analysis and machine learning approaches to model acceptable occupancy levels across multiple transport modes, including passenger cars, taxis, tourist buses, and public buses. The problem is formulated as a predictive mapping between multidimensional input variables and occupancy acceptance levels, modeled using both probabilistic and nonlinear function approximation methods. The results highlight that age, gender, and area of residence are the most significant determinants of occupancy acceptance, while education level has limited predictive relevance. Furthermore, a multi-layer feedforward artificial neural network is developed to capture nonlinear relationships between variables, achieving strong predictive performance (minimum MSE = 0.0089). The main contribution of this research lies in linking behavioral data with predictive modeling to quantify acceptable occupancy thresholds and support realistic simulation of passenger responses in crisis conditions. The proposed modeling framework contributes to transport system planning, enabling data-driven capacity management, enhanced safety strategies, and improved resilience of passenger transport operations. Full article

Urban accessibility is commonly evaluated using static spatial indicators, which assume stable travel conditions throughout the day. Road congestion, network saturation, and service variability change the function and experience of the built environment (BE). This study tests the Temporal City Framework (TCF) by examining how time of day (TOD) reshapes urban accessibility and travel behaviour with varying levels of congestion. Using 30,288 trip records from the 2022 US National Household Travel Survey (NHTS), duration is operationalised as a sixth dimension of the BE. A time-normalised impedance metric, measured in minutes per mile (MPM), is used that captures realised congestion independently of distance. Temporal impedance (TI) varies strongly with TOD, with substantially higher MPM during peak and midday periods than at night. Compared with nighttime conditions, midday travel requires approximately 19% more time per mile. This indicates a measurable contraction in functional accessibility under identical BE conditions. The TI model outperforms duration-only models, with impedance remaining dominant when both measures are included. These results support interpreting duration as a structural dimension of urban accessibility. TI significantly increases the relative likelihood of active and public transport compared to private cars, even after accounting for absolute trip duration. Hired transport modes (taxi and ride-hailing services) are most prevalent at night, reflecting a greater reliance on on-demand services outside regular daytime schedules. This study tests duration as a structural dimension of the BE by operationalising time-normalised TI. Associations are interpreted as trip-level behavioural constraints rather than causal effects. Planning frameworks based on static travel times systematically misrepresent exposure, equity, and travel mode feasibility. Time-stratified accessibility metrics should therefore be integrated into transport and land-use evaluation and associated policies. Full article

Public transportation (PT) is key to breaking the vicious cycle of private vehicles, a critical sustainability challenge in developing countries. The increase in population raises the number of private cars, and this trend continues. PT plays a vital role in reducing car use, traffic congestion, and environmental pollution. Fare is crucial to the system’s ability to encourage passengers to use PT. It affects mobility, the quality of life, and the sustainability of the system. This study aims to examine Istanbul’s optimal fare system using the BWM (Best–Worst Method) for PT fare for the first time. Furthermore, it is the first study to compare fare structures and criteria for Istanbul, Europe’s second-largest city, where transportation affects quality of life. The most frequently used fare structures and criteria in the literature and practice were weighted by experts using BWM surveys for the Istanbul Metro. The results show that distance-based fare (DBF) (43.7%) is the best fare structure, while flat fare (FF) (12.2%) is the weakest. For the criteria weightings, benefit received (24.4%) and social equity (22.7%) are seen as superior. Finally, the impact of the criterion on the fare structure was demonstrated through analysis, and its importance for experts in evaluating PT was highlighted. Full article

Rain-induced shallow landslides persistently disrupt Nepal’s mountain roads, frequently leading to fatalities, transport disruptions, and economic losses. This study develops physically validated, site-specific rainfall thresholds for the landslide-prone Kanti National Roadway (H37) by integrating empirical intensity–duration (I-D) analysis, antecedent rainfall metrics, and satellite-derived soil moisture data. Using 35 years of rainfall records (1990–2024) and 59 field-verified landslides (2017–2024), we derived a localized I-D threshold: I = 19.37 × D^−0.6215 (I: rainfall intensity in mm/h; D: duration in hours), effective for durations of 48–308 h, encompassing short intense storms and prolonged moderate rainfall. The Cumulative Antecedent Rainfall (CAR) method associated most failures with 3-day totals, while the Antecedent Precipitation Index (API) showed superior performance, with a 10-day threshold of 77 mm capturing all events. For physical validation, NASA’s SMAP Level-4 root-zone (0–100 cm) soil moisture data revealed a 1-day lag in response to rainfall; after adjustment, trends matched API saturation predictions and identified an inverse rainfall–moisture pattern before the 11 August 2019 landslide, indicating a potential instability precursor. This integration enhances predictive accuracy, bolsters mechanistic understanding of landslide hazards, and offers a scalable, cost-effective early-warning framework for data-scarce mountain regions, aiding climate-resilient infrastructure in regions with intensifying rainfall extremes. Full article

Walkability has reemerged as a central interest within planning, public health, and built environment research, yet evidence demonstrates that new urban extensions or emerging New Towns across England continue to reproduce conditions of car dependency and limited active travel options. This paper examines the structural, spatial, and sociocultural factors shaping walkability through an in-depth analysis of five residential case studies. It draws on spatial analysis and assessment of resident behaviour using sociodemographic data. Findings indicate significant disparities in walkability outcomes, with some developments characterised by fragmented layouts, weak public transport integration, and environments that make walking impractical or undesirable. The paper argues that walkability must be understood as a multidimensional, relational property of place, rather than a static design feature. The current dominant planning practices continue to prioritise vehicular access and associated infrastructure, undermining national goals for decarbonisation, health equity, and sustainable mobility. Thus, this study identifies the spatial, governance, and policy conditions necessary to deliver genuinely walkable neighbourhoods and highlights the systemic barriers that continue to constrain progress. The findings offer critical insights for planners, policymakers, and developers seeking to create environments that support healthier, more equitable, and less car dependent futures. Full article

On the basis of data from ten semi-structured interviews and selected secondary data from surveys conducted by the Office for National Statistics in Great Britain, this paper explores how young men and women articulate attitudes and experiences related to sustainable transport, using gender as an analytical lens. The study is exploratory and qualitative. Both traffic safety and personal safety appear to have a much more limiting influence on women’s travel mode choices than on men’s. Perceptions of safety, comfort, distance, convenience and accessibility are defined and shaped by the surrounding urban environment and transport infrastructure, and emerge as important considerations in the narratives of the study participants. The use of the car by men and women is somewhat linked to barriers to sustainable transport, such as infrequent and unreliable public transport, and, in the case of women, safety concerns. Concern for the environment is largely similar across male and female participants. Full article

Background: Regulations in some countries of the world allow self-driving vehicles (private cars and robo-taxis) to operate on geofenced, public roads, yet governments are slow to plan as how best to use this automated technology. We pose research questions about the Australian government’s preparedness, planning gaps for a transition to an autonomous public transport system, and specific system components that require attention. Method: We review the relevant literature, and podcasts of automobile manufacturing experts, and draw on our extensive professional experience advising governments in applying the systems approach to a planning system that includes autonomous transport. Results: Governments must include risk management in Type-II road corridors; develop mobility hubs that connect terminals for fully self-driving vehicles and robo-taxis to connect with public transport systems; and include body corporates when engaging the community in precinct planning. In the discussion, we argue the case for an autonomous urban public transport system where private ownership of vehicles is progressively reduced. Conclusions: Australian governments are not prepared with a systems-wide urban planning process that includes autonomous transport and self-driving vehicles. During the transition period, the existing and new transport systems must operate together, emphasising the leading role for governments. A roadmap for further research and development is outlined and this could provide the framework for urban planning in other jurisdictions. Full article

Urban transportation systems face increasing sustainability challenges due to the dominance of private-car use, particularly for short-distance trips. This study investigates the potential of micromobility to replace private-car travel on short-distance journeys and evaluates the resulting impacts on urban transportation networks and environmental sustainability. The analysis focuses on the Bornova district of Izmir and is based on a face-to-face survey conducted with 502 private-vehicle users. Survey data were analyzed using descriptive statistics, chi-square tests and a binary logit regression model to identify factors influencing the willingness to adopt micromobility. Within the surveyed sample of private-car users, modal-shift rates were estimated as 35% for trips up to 5 km and 33% for trips between 5 and 10 km. These rates were applied to the private-car demand and distance matrices developed for the year 2030 within the scope of the Izmir Transportation Master Plan, resulting in a revised private-car demand matrix and a separate demand matrix representing potential micromobility users. Network assignments were performed in the PTV VISUM modeling environment. Assignment results demonstrate notable network-level changes following micromobility integration. The total length of road segments with micromobility traffic volumes exceeding a threshold of 10 veh/h was calculated at 292.5 km. Environmental impacts were evaluated using a life-cycle assessment (LCA) framework, revealing an approximate 5.5% reduction in total life-cycle CO₂ emissions. Overall, the findings provide quantitative evidence supporting micromobility as an effective component of sustainable urban transport strategies and offer guidance for local governments in infrastructure planning and policy development. Full article

The flying car, academically known as electric vertical takeoff and landing (eVTOL) aircraft, is one of the core vehicles for low-altitude transportation. The split-type tilt-rotor cargo flying vehicle that is composed of tilt rotors, a fixed wing, and a detachable cargo pod exhibits characteristics of rotor–wing coupling and significant changes in weight and center of gravity (CG). Therefore, empirical design rules for conventional aircraft are not directly applicable. This paper presents the stability analysis of two configurations, i.e., the aerial vehicle module (AVM) and the aerial cargo configuration (ACC). The dynamic model of the proposed cargo flying vehicle is developed. Based on test data from the tilt-rotor experimental bench, the CFD models of the rotor subsystems and the full vehicle were validated and subsequently used to simulate the aerodynamic performance and stability of the flying vehicle under various operating conditions. The results indicate that vertical takeoff and landing (VTOL) stability is highly sensitive to the rotor–CG lever arm. Under cruise conditions, the CG positions were tested within a range of 1.4–1.7 $c_A$ (mean aerodynamic chord) from the wing leading edge with the most favorable static stability observed at 1.62 $c_A$. Among the three proposed tilt-rotor strategies, initiating the secondary tilt rotors first while keeping the main tilt rotors vertical results in the weakest rotor–surface aerodynamic coupling, the lowest pitching-moment peaks, and favorable longitudinal static stability. These findings inform CG management, aerodynamic layout, and tilt-schedule design for split-type tilt-rotor cargo vehicles in low-altitude transportation. Full article

The transportation sector’s decarbonization represents one of the most critical challenges in achieving global climate targets. This study presents a comprehensive analysis of an integrated renewable energy system that produces green hydrogen through a hybrid solar photovoltaic (PV) and wind power configuration. The proposed system combines a 1.2 MWp solar array with 800 kW wind turbines, feeding a 1 MW proton exchange membrane (PEM) electrolyzer for hydrogen production. The hydrogen is subsequently compressed, stored at 350 (for trucks and buses) and 700 bar (for cars), and then utilized either directly for fuel cell electric vehicles (FCEVs) or reconverted to electricity via a 250 kW stationary PEM fuel cell to support electric vehicle (EV) charging infrastructure. Through detailed techno-economic simulation using HOMER Pro and MATLAB/Simulink 2022a, we demonstrate that the hybrid configuration achieves a 71% electrolyzer capacity factor, producing 55.8 tonnes of hydrogen annually with a levelized cost of 5.82 €/kg. The system ensures over 60 h of grid-independent operation while reducing CO₂ emissions by 1656 tones annually compared to conventional grid-powered alternatives. Results indicate that hybrid renewable hydrogen systems can provide economically viable solutions for sustainable mobility infrastructure, with projected cost reductions making them competitive with fossil fuel alternatives by 2030. Full article

Transport decarbonization and electrification are the current concepts of sustainable logistics. The European Green Deal aims to remove internal combustion engine vehicles from the roads and make the continent climate neutral by 2050. However, there is much debate about the means to achieve this goal and the rivalry between diesel and electric vehicles. This article aims to analyze the impact of the energy efficiency of diesel and electric vehicles on the sustainability of urban logistics and the benefits for the average transport user—the driver. The study uses scientific literature, statistical, comparative, SWOT analysis methods, and experimental research methods. In addition, a qualitative study was conducted with the help of experts, and the problematic relationships between diesel and electric vehicles were analyzed. The results of the study showed that even an old diesel vehicle is not inferior to a new electric vehicle in terms of energy efficiency and operation for the average user but does not meet the theoretical sustainability standards for urban logistics. Therefore, broader apolitical discussion and practical experiments are needed to ensure that the results of future research are unbiased. Full article

Public transport is vital for social and economic life, but many people with disabilities still face exclusion due to both physical and psychosocial barriers. This study examined how psychosocial barriers influence public transport travel behavior among people with mobility, vision, and hearing disabilities in the City of Tshwane, South Africa. A quantitative survey was conducted using a structured questionnaire among 214 respondents. The results showed that fear of crime, lack of personal safety, anxiety when travelling alone or to unfamiliar places, and negative treatment by drivers and co-passengers are major deterrents to public transport use. Psychosocial barriers were significantly associated with travel behavior and a strong preference for private cars as well as ride-hailing services. Group comparisons revealed that individuals with vision disabilities experience significantly higher levels of transport-related fear compared to other groups. People with mobility and vision disabilities are more affected by negative attitudes from co-passengers compared to people with hearing disabilities. Psychosocial barriers are associated with low trip frequencies for non-essential activities, indicating suppressed travel. The study concludes that achieving inclusive urban mobility requires addressing psychosocial barriers alongside physical accessibility to ensure safe, dignified, and independent travel for people with disabilities. Full article

Transport is one of the few major sectors in Europe where greenhouse gas emissions have not declined despite tightening climate policy. Road transport remains dominated by fossil fuels, rising travel demand, and growing freight activity. This paper develops a multi-indicator benchmarking framework to assess the extent to which recent road-transport developments in EU-27 Member States align with structural expectations derived from 1.5 °C and 2 °C mitigation pathways. A multi-indicator framework is developed combining emissions and air-quality pressures, system drivers, and urban accessibility for 2019–2023, using harmonized Eurostat, European Environment Agency, WHO, and OECD data. The analysis follows a dual-track design. First, hierarchical agglomerative clustering identifies national transport–climate profiles. Second, PROMETHEE II is applied to generate an outranking-based performance index and country ranking. Five distinct clusters emerge, ranging from carbon-intensive, car-dependent systems with limited electrification and weak accessibility to “sustainability leaders” characterized by lower emissions, higher shares of low-emission vehicles, and strong public-transport accessibility. PROMETHEE results align with this typology: Nordic and north-western countries rank highest, while several southern and eastern countries show negative net flows linked to persistent car dependence, slower fleet transition, and higher pollution exposure. The results suggest that while several countries demonstrate structural progress toward transport decarbonization, none exhibit a performance profile fully consistent with transition patterns associated with 1.5 °C-aligned mitigation pathways. Full article