新冠肺炎疫情对民航的影响分析与政策建议

为给政府制定应对策略提供决策支持，基于航班运行数据分析了新型冠状病毒肺炎疫情对民航造成的影响。通过分析2003年“非典”和新型冠状病毒肺炎疫情对民航影响的差异，基于情景假设对2020年民航运输发展形势进行了预测分析，并提出有关政策建议。研究结果表明：新型冠状病毒肺炎疫情对民航市场需求造成了严重的冲击，2020年民航运输形势不容乐观，预计年旅客运输量同比基本持平或下降10.9%。政府部门需在做好疫情防控期间运输保障工作的同时，加快出台积极的产业政策以支撑民航发展。     

How the cap limit for food-crop-based biofuels may affect France’s stakeholders by 2030? A range-based multi-actor multi-criteria analysis

From 2012 to 2016, the long-term signal in the biofuel market changed almost once per year, leading to a drastic decrease in investments and contributing to multiple production unit closures in France and around Europe. The European Commission proposed a new renewable energy directive that includes a 3.8% cap limit on the contribution of food-crop biofuels by 2030. Given the role of biofuels in green growth, the bioeconomy, and renewable energy incorporation targets, how will this measure affect the stakeholders by 2030? Will it lead to, contribute to, or hamper their sustainability criteria? This paper aims to contribute to this debate by studying the case of France. To this end, our methodology—the range-based multi-actor multi-criteria analysis—aims to (1) explicitly consider the stakeholder groups and their sustainability criteria; (2) evaluate and compare how the cap limit will affect these sustainability criteria whether or not advanced biofuels are deployed by 2030; (3) capture the uncertainty of the context evolution and biofuel capacity to fulfil the stakeholders’ sustainability criteria by means of a Monte Carlo. The results suggest that the cap limit is a double-edged sword for the stakeholders and their sustainability criteria. Shifting towards advanced biofuels while limiting the food-crop biofuels is the better alternative for most of the stakeholders. Nevertheless, given biofuel policy instability and the lost confidence of investors, such a shift may not occur by 2030. In such a case, this paper demonstrates that the cap limit may highly and negatively affect the stakeholders and their sustainability targets, whereas fostering French food-crop biofuel production at its full capacity level constitutes a better alternative. As no alternative is suited to all actors simultaneously, this paper also studies the strengths and weaknesses of these alternatives from each stakeholder groups’ perspective.     

Human-like autonomous car-following model with deep reinforcement learning

This study proposes a framework for human-like autonomous car-following planning based on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation environment where an RL agent learns from trial and error interactions based on a reward function that signals how much the agent deviates from the empirical data. Through these interactions, an optimal policy, or car-following model that maps in a human-like way from speed, relative speed between a lead and following vehicle, and inter-vehicle spacing to acceleration of a following vehicle is finally obtained. The model can be continuously updated when more data are fed in. Two thousand car-following periods extracted from the 2015 Shanghai Naturalistic Driving Study were used to train the model and compare its performance with that of traditional and recent data-driven car-following models. As shown by this study’s results, a deep deterministic policy gradient car-following model that uses disparity between simulated and observed speed as the reward function and considers a reaction delay of 1 s, denoted as DDPGvRT, can reproduce human-like car-following behavior with higher accuracy than traditional and recent data-driven car-following models. Specifically, the DDPGvRT model has a spacing validation error of 18% and speed validation error of 5%, which are less than those of other models, including the intelligent driver model, models based on locally weighted regression, and conventional neural network-based models. Moreover, the DDPGvRT demonstrates good capability of generalization to various driving situations and can adapt to different drivers by continuously learning. This study demonstrates that reinforcement learning methodology can offer insight into driver behavior and can contribute to the development of human-like autonomous driving algorithms and traffic-flow models.     

Sustainability and interactivity between cities and ports: a two-stage data envelopment analysis (DEA) approach

Ports and cities are intrinsically linked. Port city, which serves as a link between the local and global economy, is an integration of both urban and port systems. Constrained by different regional structures, port cities have developed various formulations over time. Using a two-stage data envelopment analysis (DEA) approach, this paper proposes a new method for measuring the sustainable development of different port city systems. While the previous empirical studies often separate the port system and the urban system, this paper assesses the two systems in an integrated way. Moreover, this paper develops a systematic methodology for measurement of sustainability. Twenty world-leading container port cities are selected for this study using contemporary data. The DEA results display their relative differences in levels of sustainable development, which reveal the effectiveness of the prevailing policies in them. Eventually, recommendations are drawn for other port cities by referring to the best practices.     

Historic vehicles: an overview from a transport policy perspective

Historic vehicles (HVs) are the heritage of road transport that have surprisingly received little attention in the academic literature. This study presents an overview of the literature on HVs, focusing on the three topics that dominate the policy debate on transport: environmental, safety and congestion impacts. We observed that polluting emissions of HVs are per kilometre much higher (often a factor 5 or more) than those of moderns vehicles. The annual average mileage per vehicle per year of HVs is much lower than other vehicles. The lower active and passive safety levels of HVs are compensated by the way these vehicles are driven, resulting in the risk factors per kilometre being roughly equal or lower than other vehicles. The contribution of HVs to congestion is negligible. However, the transport policy discourse is divided on the topic of HVs. More comprehensive and effective laws and regulation are needed to protect this aspect of the heritage of road transport whilst concurrently avoiding or limiting the problems caused by them.     

Agent-based simulation framework for mixed traffic of cars,pedestrians and trams

In this paper, we report on the construction of a new framework for simulating mixed traffic consisting of cars, trams, and pedestrians that can be used to support discussions about road management, signal control, and public transit. Specifically, a layered road structure that was designed for car traffic simulations was extended to interact with an existing one-dimensional (1D) car-following model and a two-dimensional (2D) discrete choice model for pedestrians. The car model, pedestrian model, and interaction rules implemented in the proposed framework were verified through simulations involving simple road environments. The resulting simulated values were in near agreement with the empirical data. We then used the proposed framework to assess the impact of a tramway extension plan for a real city. The simulation results showed that the impact of the proposed tramway on existing car traffic would not be serious, and by extension, implied that the proposed framework could help stakeholders decide on expansion scenarios that are satisfactory to both tram users and private car owners.     

国外海上浮动核电站政策和标准规范

在对国外海上浮动核电站相关的国际法律法规和标准规范研究现状的基础上,重点分析俄罗斯船级社和俄罗斯监察局海上浮动核电站相关标准规范,以为我国开展海上浮动核电站建设所需的标准规范研究提供参考与借鉴。     

Evaluating the effects of green port policy: Case study of Kaohsiung harbor in Taiwan

The paper evaluates the effectiveness of strategies designed to reduce these pollutants in port areas, based on a newly developed assessment model to calculate emissions. The case study found that the strategy of reducing the ship’s speed to 12 knots is most effective in cutting fuel consumption and costs, as well as emissions. Adopting an onshore power supply system could reduce CO₂ emission by 57.16% and PM by 39.4%. By adopting the strategies of both reduced speed and cold ironing emissions control, a reduction in emissions of 71% to 91% can be achieved with a 20 nautical mile reduced speed zone. Therefore, the goals of reductions in emissions to improve port areas air quality could be achieved through adopting a green port policy in the future.     

杭州地下空间发展展望与研究

地下空间作为城市有机体的一部分,在未来城市建设中担任着重要的角色。文章分析杭州城市地下空间(地下交通设施、地下综合体、地下市政设施、人防设施)发展的特点。从开发总量与人均水平、空间分布与开发深度、开发功能3个方面介绍杭州市地下空间开发利用的现状,分析其存在的问题主要为政策及管理方面与功能开发方面。同时介绍未来杭州地下城的发展策略,并展望其发展蓝图。最后分析杭州市地下空间开发建设过程中亟待思考与解决的工程技术问题,包括:特殊地质及工程技术问题(粉土、粉砂地层,淤泥地层,上软下硬地层等问题;近接施工技术,地下立交技术等)、地下工程防灾问题、景区环境保护问题、地下空间全生命周期数字化工程。     

“公交优先”战略下清远市公交发展研究

交通拥堵和交通污染问题是近年来引人关注的问题,特别是交通碳减排已成为发达国家碳减排的重点领域,而优先发展公交系统对解决上述问题具有重大的现实意义。在总结和阐述公交优先发展的内涵和意义的基础上,以清远市公交系统为研究对象,总结和分析了"公交优先"战略下清远市公交发展现状和问题,提出了清远市公交优先发展的思路与具体做法,并根据现有情况规划了三种不同水平的公交优先发展情景方案,计算了三种方案下二氧化碳的排放量。结果显示:公交很高吸引力的方案比一般吸引力的方案每年少排二氧化碳38.9万t,年度减排直接效益为2 723万元,节约能源的直接效益为12.5亿元。最后提出了清远市公交优先发展的政策建议。