Rapid urban growth in Gulf Cooperation Council (GCC) countries has increased traffic exposure and crash risk, creating the need for locally calibrated safety models. This study develops a Bayesian spatio-temporal framework to estimate Safety Performance Functions (SPFs) across more than 57,000 road segments in Abu Dhabi. Police-reported injury crashes from 2013–2020 are modelled using a Negative Binomial specification within the INLA framework, incorporating roadway characteristics, exposure measures, continuous spatial dependence, and an annual effect.The results show a clear safety hierarchy: junction links (intersections and roundabouts) experience several times the crash frequency of mid-block segments, which all sit below the network average, while higher traffic volume, free-flow speed, and number of lanes are each associated with elevated crash frequency. The relationship between volume-to-capacity ratio and crash frequency is broadly increasing, with crash risk elevated under denser and over-saturated conditions. The annual effect shows a reduction in 2020 consistent with COVID-19 mobility restrictions.Using a continuous spatial field (SPDE), this study identifies a spatial influence radius of about 2–3 km, a locally calibrated screening reference for corridor bundling and control-site selection that complements, rather than replaces, existing buffer techniques. The framework delivers interpretable, locally calibrated safety parameters that support transparent and cost-effective investment decisions in rapidly motorising metropolitan networks.
Understanding the socioeconomic performance of transport hubs and corridors is essential for designing resilient transportation systems and effective regional development policies. Existing assessments, however, often focus on isolated infrastructure components or rely on weakly validated indicators. This study develops a hub-corridor evaluation framework that links transportation structure with regional economic dynamics and household income. Indicator weights are derived using the Type-1 Fuzzy Best-Worst Method with triangular fuzzy numbers. A panel of 12 experts provides individual pairwise comparisons. Each expert independently identifies their best and worst indicators. Individual consistency is verified through the Fuzzy Consistency Ratio with a feedback revision cycle ensuring R(FCR) ≤ 0.1. Individual fuzzy weights are aggregated using the weighted geometric mean, and a Group Consensus Index diagnoses the level of expert agreement. The framework is empirically applied to four transport hubs in China’s Chengdu-Chongqing urban agglomeration. The ranking places Hub 1 first, followed by Hub 2, Hub 3, and Hub 4. Notably, Hub 1 outperforms the physically larger Hub 2 due to its balanced strengths in household transport affordability and spatial efficiency. Monte Carlo simulations with 1,000 weight perturbations confirm a completely stable ranking. The analysis reveals three resilience profiles: balanced hubs achieving synergies across multiple dimensions, economic-driven hubs generating strong agglomeration benefits but facing socio-ecological vulnerabilities, and latent hubs with infrastructure capacity underutilized by weak regional demand. Socioeconomic resilience depends less on transport scale than on alignment between hub capacity, corridor operation, and regional economic structure. These findings offer actionable guidance for policymakers to diagnose structural mismatches and prioritize resilience-enhancing investments. From a policy perspective, the proposed framework provides a transparent and replicable tool for identifying vulnerabilities and supporting context-sensitive strategies in rapidly urbanizing regions.
The proliferation of in-vehicle infotainment systems raises critical safety concerns regarding driver distraction. This driving simulator study provides empirical evidence on how interaction modalities (touchscreen, voice, gesture) for non-driving-related tasks (NDRTs) affect driver state under varying traffic density and lighting conditions. Results showed that touchscreen interaction was associated with higher workload-related EEG activity, reduced HRV, larger eyelid aperture, lower situation awareness (SA), and less stable vehicle-control measures. Nighttime driving was associated with larger pupil diameter, while some adverse modality-related outcomes were more pronounced under high-density nighttime conditions. In contrast, voice interaction and WoZ-implemented gesture interaction were associated with lower workload-related indicators under the present controlled simulator conditions. A layered SA analysis revealed that perception-level SA was primarily impaired by visually demanding touchscreen use, while comprehension- and projection-level SA were more affected by environmental complexity. Within the scope of this driving simulator study—focusing on a music-selection task among young drivers—the proposed multimodal assessment framework contributes empirical evidence that may inform situation-aware adaptive interface design and scenario-based evaluation approaches for integrated HMI systems. These findings caution against overreliance on touchscreen interfaces for music-selection tasks in complex driving environments and suggest the potential safety relevance of lower-visual-demand modalities such as voice interaction and controlled gesture interaction, while recognizing that production-grade gesture recognition may introduce additional recognition-related costs.
This paper investigates the determinants of aircraft ground delays, defined as excess time spent during taxiing and turnaround, using a dataset of domestic flights in mainland China in 2023. As one of the first studies to examine aircraft ground delays in China’s regulated aviation market, we use a two-stage least squares (2SLS) model to analyze flight-, airline-, and airport-level factors, with a focus on scheduling buffers (outbound flight buffers and ground buffers). The results show that longer outbound flight buffers are associated with longer ground delays, whereas longer ground buffers reduce ground delays. The outbound flight-buffer effect operates partly through increased gate holding and is stronger on longer-haul flights; it is also more pronounced when the inbound flight arrives late and when daily aircraft utilisation is lower. Ground delays are further higher for full-service airlines, larger aircraft, longer routes, and more congested airports. Component analyses indicate that earlier legs in an aircraft’s daily rotation tend to have longer boarding times, while late-arriving inbound flights are associated with longer taxi-out times. Regional heterogeneity is evident: the outbound flight-buffer effect is most pronounced in eastern China, where an additional outbound flight buffer more often translates into extra ground time due to boarding and gate holding. Within the Beijing–Tianjin–Hebei cluster, airlines with larger market shares experience longer delays, with longer gate hold and taxi-in times, indicating a shift in waiting from taxiways to gates. These insights inform both airline scheduling strategies and airport policies aimed at mitigating ground delays.
The U.S. Section 301 investigation against China’s maritime industry and the resulting differentiated port service fees constitute a novel trade policy intervention with potential implications for Sino–U.S. shipping routes. To examine this policy shift, this study constructs a policy intensity index (PII) based on official policy documents and evaluates the evolution of logistics efficiency on Sino–U.S. liner routes over the 2023–2025 period. The DEA-BCC model and Malmquist index are applied to evaluate logistics efficiency from both static and dynamic perspectives, while a rolling-window VAR model is employed to examine the association between efficiency fluctuations and exports to seven major trading partners. The results show that comprehensive efficiency (Crste) varies with policy intensity, reaching its sample-period low of 0.667 in November 2025 following the formal implementation of port service fees. Scale efficiency (Sech) is the primary source of variation, while pure technical efficiency (Vrste) remains stable throughout the sample period. Furthermore, the rolling-window VAR results reveal a positive and significant association between efficiency changes and exports for the EU and ASEAN, a finding that remains robust even after controlling for tariff rates. These findings highlight that route efficiency varies with policy intensity and that the efficiency–export linkage differs across trading partners.
