•Concepts of transport system vulnerability and resilience are defined and discussed.•Recent research on transport system vulnerability and resilience is reviewed.•Topological and system-based ...vulnerability studies are two distinct traditions.•Merits and drawbacks of these two traditions are discussed.•Cross-disciplinary collaboration helpful to exploit the potential of the research.
The transport system is critical to the welfare of modern societies. This article provides an overview of recent research on vulnerability and resilience of transport systems. Definitions of vulnerability and resilience are formulated and discussed together with related concepts. In the increasing and extensive literature of transport vulnerability studies, two distinct traditions are identified. One tradition with roots in graph theory studies the vulnerability of transport networks based on their topological properties. The other tradition also represents the demand and supply side of the transport systems to allow for a more complete assessment of the consequences of disruptions or disasters for the users and society. The merits and drawbacks of the approaches are discussed. The concept of resilience offers a broader socio-technical perspective on the transport system’s capacity to maintain or quickly recover its function after a disruption or a disaster. The transport resilience literature is less abundant, especially concerning the post-disaster phases of response and recovery. The research on transport system vulnerability and resilience is now a mature field with a developed methodology and a large amount of research findings with large potential practical usefulness. The authors argue that more cross-disciplinary collaborations between authorities, operators and researchers would be desirable to transform this knowledge into practical strategies to strengthen the resilience of the transport system.
The introduction of functional splits in C-RANs brings a tradeoff between radio performance and transport capacity. Higher-layer splits relax transport capacity requirements, whereas radio ...performance is not guaranteed. Lower-layer splits are beneficial for the radio performance, but they may require a more expensive and high capacity transport network. Facing the challenge of how to deploy 5G RANs in the short-term future, network operators need to find the best functional split options able to accommodate radio performance requirements without incurring excessive transport network costs. This article presents an architecture referred to as F-RAN able to choose the most appropriate split option while considering time-varying radio performance and the availability of transport resources. F-RAN can accommodate these needs by means of an SDNbased orchestration layer and a programmable optical transport network. The performance of F-RAN is benchmarked against a conventional C-RAN architecture in terms of the number of wavelengths and transponders to be deployed. Simulation results confirm the overall benefits of F-RAN in terms of better utilization of transport resources.
Factors such as inclement weather or manmade destruction greatly impact the traffic efficiency of the whole air transport network. As China’s air transport network (CATN) becomes a large network ...system, understanding how it will be affected by unexpected events becomes increasingly important. We investigated the robustness of CATN over 40 years due to random failures and targeted attacks, from not only a topological but also a spatiotemporal viewpoint. When subjected to random failures, CATN shows enhanced robustness with more than 80% of airports being required to fail for network paralysis. When subjected to targeted attacks, CATN’s robustness is dominated by 20% of airports. Western parts of CATN are always more vulnerable than the eastern parts, and most long-distance routes fail while short-distance routes are less affected by early attacks. We defined the subnetwork comprising 20% of airports as the trunk network of CATN according to the attacks based on betweenness centrality, which is found to be the most effective way to cause a collapse comparing with attacks based on degree and closeness centrality.
•The impact of airport failures on China air transport network over 40 years are assessed.•80% of airports fail or 20% of airports attacked can lead to the paralysis of China air transport network.•The spatial fragmental process of China air transport network under simulated attacks is presented.•Trunk networks of China air transport are extracted from the view of robustness.
•Unique review of resilience and vulnerability in transportation science.•Resilience and vulnerability are seen from a connectivity and accessibility angle.•Both concepts are related to robustness, ...reliability and friability.
This paper aims to adopt a critical stance on the relevance and interpretation of the recently emerging concepts of resilience and vulnerability in transportation studies. It makes a clear distinction between engineering and ecological interpretations of these concepts and offers a systematic typology of various studies in this field. A core element in the study is the linkage between the aforementioned concepts and connectivity/accessibility in transport networks. The methodological findings in the study are put in perspective by addressing also such concepts as robustness, reliability and friability of transport systems.
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•An advanced network model was developed to analyze PM2.5 and O3 transport dynamics.•Spatiotemporal difference in PM2.5 and O3 transport dynamics was revealed.•Spillover pathways of ...PM2.5 and O3 among cities and provinces were identified.•PM2.5 and O3 zones were divided using network weights and the GN algorithm.•The model accuracy was validated by comparing with the WRF-CAMx simulation.
Air pollution exhibits significant spatial spillover effects, complicating and challenging regional governance models. This study innovatively applied and optimized a statistics-based complex network method in atmospheric environmental field. The methodology was enhanced through improvements in edge weighting and threshold calculations, leading to the development of an advanced pollutant transport network model. This model integrates pollution, meteorological, and geographical data, thereby comprehensively revealing the dynamic characteristics of PM2.5 and O3 transport among various cities in China. Research findings indicated that, throughout the year, the O3 transport network surpassed the PM2.5 network in edge count, average degree, and average weighted degree, showcasing a higher network density, broader city connections, and greater transmission strength. Particularly during the warm period, these characteristics of the O3 network were more pronounced, showcasing significant transport potential. Furthermore, the model successfully identified key influential cities in different periods; it also provided detailed descriptions of the interprovincial spillover flux and pathways of PM2.5 and O3 across various time scales. It pinpointed major pollution spillover and receiving provinces, with primary spillover pathways concentrated in crucial areas such as the Beijing-Tianjin-Hebei (BTH) region and its surrounding areas, the Yangtze River Delta, and the Fen-Wei Plain. Building on this, the model divided the O3, PM2.5, and synergistic pollution transmission regions in China into 6, 7, and 8 zones, respectively, based on network weights and the Girvan Newman (GN) algorithm. Such division offers novel perspectives and strategies for regional joint prevention and control. The validity of the model was further corroborated by source analysis results from the WRF-CAMx model in the BTH area. Overall, this research provides valuable insights for local and regional atmospheric pollution control strategies. Additionally, it offers a robust analytical tool for research in the field of atmospheric pollution.
A series of composite gel polymer electrolytes (GPEs) based on poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), 1-ethtyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ...(EMIMTFSI), lithium bis(trifluoromethane) sulfonimide (LiTFSI) and covalent linked 2,2''-(ethylenedioxy) bis (ethylamine) to reduced graphene oxide (rGO-PEG-NH2) have been successfully prepared by solution casting method. With the increase of EMIMTFSI and rGO-PEG-NH2 content, the crystallinity of the GPE decreased, and the thermal decomposition temperature increased significantly. A high-speed lithium ion transport network was formed in the 3P5E2LG-10 GPE, with rGO as the connection site and PEG as the bridge. 3P5E2LG-10 GPE exhibited a conductivity of 2.1 × 10−3 S cm−1 at 30 °C, a lithium ion transference number of 0.45, and a electrochemical window of 5.0 V. The 3P5E2LG-10 based cell exhibited more than 99% columbic efficiency and the initial discharge capacity reached the maximum of 163.7 mAh/g, and capacity retention was about 88% after 80 cycles at 0.1C. 3P5E2LG-10 GPE will have great potential for lithium ion battery with high safety and long cycle life.
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•EMIMTFSI and rGO-PEG-NH2 decrease the crystallinity of PVDF-HFP and promote transmission of lithium ion.•3P5E2LG-10 exhibits 2.1 × 10−3 S cm−1, a lithium ion transference number of 0.45, and a electrochemical window of 5.0 V.•The electrolyte has excellent cycle performance and good inhibitory effect on the growth of lithium dendrites.
The COVID-19 pandemic crisis has greatly impacted public transport ridership and service provision across the world. As many countries start to navigate their return to normality, new public ...transport planning requirements are devised. These measures imply a major reduction in service capacity compared to the pre-COVID-19 era. At the time of writing, there is a severe lack of knowledge regarding the potential impact of the pandemic on public transport operations and models that can support the service planning given these new challenges. In this literature review, we systematically review and synthesise the literature on the impacts of COVID on public transport to identify the need to adjust planning measures, and, on the other hand, the existing methods for public transport planning at the strategic, tactical and operational level. We identify intervention measures that can support public transport service providers in planning their services in the post-shutdown phase and their respective modelling development requirements. This can support the transition from the initial ad-hoc planning practices to a more evidence-based decision making.
•A stacked bidirectional and unidirectional LSTM architecture for traffic forecasting.•An LSTM structure with an imputation unit to infer missing values is proposed.•The trade-off between model ...capacity and complexity is evaluated.
Short-term traffic forecasting based on deep learning methods, especially recurrent neural networks (RNN), has received much attention in recent years. However, the potential of RNN-based models in traffic forecasting has not yet been fully exploited in terms of the predictive power of spatial–temporal data and the capability of handling missing data. In this paper, we focus on RNN-based models and attempt to reformulate the way to incorporate RNN and its variants into traffic prediction models. A stacked bidirectional and unidirectional LSTM network architecture (SBU-LSTM) is proposed to assist the design of neural network structures for traffic state forecasting. As a key component of the architecture, the bidirectional LSTM (BDLSM) is exploited to capture the forward and backward temporal dependencies in spatiotemporal data. To deal with missing values in spatial–temporal data, we also propose a data imputation mechanism in the LSTM structure (LSTM-I) by designing an imputation unit to infer missing values and assist traffic prediction. The bidirectional version of LSTM-I is incorporated in the SBU-LSTM architecture. Two real-world network-wide traffic state datasets are used to conduct experiments and published to facilitate further traffic prediction research. The prediction performance of multiple types of multi-layer LSTM or BDLSTM models is evaluated. Experimental results indicate that the proposed SBU-LSTM architecture, especially the two-layer BDLSTM network, can achieve superior performance for the network-wide traffic prediction in both accuracy and robustness. Further, comprehensive comparison results show that the proposed data imputation mechanism in the RNN-based models can achieve outstanding prediction performance when the model’s input data contains different patterns of missing values.
In Switzerland, strict measures as a response to the Covid-19 pandemic were imposed on March 16, 2020, before being gradually relaxed from May 11 onwards. We report the impact of these measures on ...mobility behaviour based on a GPS tracking panel of 1439 Swiss residents. The participants were also exposed to online questionnaires. The impact of both the lockdown and the relaxation of the measures up until the middle of August 2020 are presented. Reductions of around 60% in the average daily distance were observed, with decreases of over 90% for public transport. Cycling increased in mode share drastically. Behavioural shifts can even be observed in response to the announcement of the measures and relaxation, a week before they came in to place. Long-term implications for policy are discussed, in particular the increased preference for cycling as a result of the pandemic.
•Understanding of the change in mobility patterns in Switzerland using a large GPS Panel during the Covid19 Pandemic.•Evidence for a large increase in cycling kilometers during the first lockdown which was sustained into the summer.•Changes in mobility behaviour varied across different socio-demographic groups.
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