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The article focuses on the evaluation of the impact of air traffic interruptions with regard to the number of submitted occurrences reports which were received by AAII (Air Accident Investigation Institution). The article is aimed at evaluating the current legislation, according to which there is an obligation to report, as well as identifying trends in occurrence reporting with a focus on changing the number of reports in the period of forced “shutdown” of air transport in connection with COVID19 and subsequent evaluation of the findings.

While the COVID-19 pandemic is hammering trade around the world, China and ASEAN have managed to buck the trend with a 5% growth this year, and ASEAN has become China's largest trading partner. International road transport plays an important role in the circulation of goods and people, contributing to the economic growth and trade facilitation in the region. This paper analyzes the international road transport situation in China-ASEAN Area, combs the problems it faced, draws lessons from the EU, and makes suggestions (i.e., strengthen infrastructure construction, expand the scope of international road transport, deepen transportation cooperation among countries, speed up the establishment of coordination mechanism, establish emergency transportation security system) for better China-ASEAN economic and trade cooperation.

The outbreak of COVID-19 has brought the world to a standstill. More than half of the world's population was in lockdown at the beginning of April. People were urged not to go out and avoid public transport. A few figures to take stock of the situation: around 4 billion people subject to various movement restrictions worldwide, air traffic is reduced by about 90% and shared mobility platforms activity reduced to 2% to 5% of their regular business. The current crisis, which is impacting both the supply and demand for transport, appears to be a privileged moment to rethink mobility and place it on a more sustainable trajectory. The Covid-19 crisis has a significant repercussion on demand and supply of mobility in Victoria as the Victorian government has put citizens in lockdown to limit the spread of COVID-19. This research aims to investigate the travel containment measures (government restrictions) taken in response to the COVID-19 emergency have on Victorian's mobility as this insight is vital to estimate parameters appropriate for the different stages of the crisis, before and after the implementation of prevention policies.

This paper is to introduce the remote ATC simulation tutoring assistant tool, E-tutoring tool for short, which aims to solve the problem of lack of instructors for managing ATC simulation training and adhering to restrictions such as COVID-19 social distancing requirements. The ratio of students to the instructor in the ATC simulation room is currently 6 to 1. One instructor must observe 4 students who are simultaneously doing an ATC simulation exercise. The maximum capacity of this course is 30 students per semester. By using the E-tutoring tool, we aim to mirror the students’ real-time practice scenario to a remote computer screen that can be observed by a remote ATC instructor. At the same time, the ATC instructor can communicate with the students to help them improve their practical skills. There are several benefits to applying the E-tutoring tool. Firstly, the remote instructor is not required to be present on campus, which results in huge benefits for instructors who live far from the campus and where the tutoring time needs to be very flexible, or in situations where COVID social distancing rules apply and it is not feasible to allow instructors to be in a limited space with students. In addition, the availability of increased numbers of remote instructors means that the number of student enrolments can be increased. Secondly, the teaching of ATC skills requires a lot of engagement with ATC instructors. With the E-tutoring tool, each student will receive more personalized attention and they will consequently be motivated to learn and perform better, have a better learning experience. Thirdly, such innovation in blended and online education aligns with the future of education and will result in high-quality teaching, cost-effectiveness and improved efficiency. Last but not least, some experimental results will be presented to show the output of the application of E-tutoring tool. In conclusion, the development of the E-tutoring tool will have a very positive impact on the current air space management course and offer more enrolment opportunities for students without compromising the quality of this course.

Part 5: Autonomous Agents; International audience; Autonomous Vehicles (AVs) can potentially reduce the accident risk while a human is driving. They can also improve the public transportation by connecting city centers with main mass transit systems. The development of technologies that can provide a sense of security to the passenger when the driver is missing remains a challenging task. Moreover, such technologies are forced to adopt to the new reality formed by the COVID-19 pandemic, as it has created significant restrictions to passenger mobility through public transportation. In this work, an image-based approach, supported by novel AI algorithms, is proposed as a service to increase autonomy of non-fully autonomous people such as kids, grandparents and disabled people. The proposed real-time service, can identify family members via facial characteristics and efficiently ignore face masks, while providing notifications for their condition to their supervisor relatives. The envisioned AI-supported security framework, apart from enhancing the trust to autonomous mobility, could be advantageous in other applications also related to domestic security and defense.

The transport sector continues to be the greatest contributor to the alarming emission levels. In fact, today more than ever, people favor the use of passenger vehicles over public transport to avoid contact with coronavirus. Carbon savings made across the sectors during the global lockdown to control the spread of the novel COVID-19 virus are therefore at a great threat. This necessitates the need for sustainable transition to an ultra-low carbon transportation system. Although, electric vehicles enablement continues to aid with transition, the sustainability of the fuel poses greater risks for pollution shifting. In this paper an DC microgrid EV charging solution powered by renewables is explored through MATLAB and HOMER simulation. A realistic approximation to carpark special constraints is calculated and a solar PV system in both S-shape and M-shape configurations is modelled. The analysis for efficient space utilisation is based on sun path data and weather conditions in the city of Leeds for a constant peak load of 10 EVs. As well as, an alternative in the form of a small wind turbine is compared with photovoltaics for a single charging station.

The importance of scheduled air transport for the existence of airports is a topic that is constantly relevant, especially during the Covid-19 pandemic, which has negatively affected operations at all world airports, disrupted its regularity and thus its direct and indirect effects on the region. This work focuses on airports dependent on the operation of scheduled air transport from several perspectives. After an initial study of the available literature on the importance of scheduled air transport for the existence of airports, we defined the terms demand and supply factors of the airport influencing scheduled air transport. One of the key parts of the work is the calculation of the critical number of airport movements, which represents the break even point in the amount of production in which the airport shows no loss but also no profit. The reasons for the abolition of scheduled air services, such as the occurrence of a military conflict near the airport or insufficient research of the demand for air traffic in the area, are described in the chapter analyzing European and global airports with canceled scheduled air traffic in individual case studies. The chapter also deals with the alternative uses of airports themselves, which were forced to terminate their function for the public. Airports and their equipment are highly specialized for use in air transport operations and therefore operators and their subsequent owners often face difficulties in finding alternative uses. An essential part of this work is an analysis of the response of selected European airports to the outbreak of Covid-19 in 2020 and a comparison of the number of passengers carried at these airports in 2019 and 2020. The final chapter contains a summary of findings and the call to change transport policies in the benefit of airports and their protection from future aviation pitfalls such as the Covid-19 pandemic.

There is increasing commercial interest in the deployment of autonomous aircraft for both passenger and cargo transport. Indeed, with the need for more human-free deliveries, the COVID19 crisis has led to a sharp spike in drone deliveries. This increased demand is putting additional stress on supporting infrastructure like air traffic control, which is already struggling with outdated technology. The recent 737 MAX crashes also highlight the complexities surrounding the development of aircraft autonomy as well as testing and certification. In order to more precisely determine whether universities are keeping pace with both research and education needs from external stakeholders in terms of aerospace autonomy, we conducted a survey that targeted aerospace leaders in academia, industry, and government. The results show there is a significant gap between the education and research aims of academia and what is needed in industry and government. To fill this gap and maintain international superiority in aerospace autonomy, the US needs to promote the convergence in the fields of computer science and aerospace engineering, as well as safety, cybersecurity, and testing. Without such transformation, the US will not be able to maintain its technological superiority in aerospace systems.

In recent years, prior to COVID-19, capacity shortfalls in airspace and airports inevitably caused an increase in aircraft delays. Therefore, when it returns to normal conditions, the airspace will exhibit the same capacity limits, even under normal weather conditions. To ensure that air traffic remains safe, reliable, and efficient in adverse weather conditions, planning and coordination activities through a Collaborative Decision Making process are required to deliver the most effective Air Traffic Flow and Capacity Management services to Air Traffic Control and Aircraft Operators. Nowadays, this task is based on air traffic controllers’ experience and historical data. That means that the Flow Manager Positions and the Network Manager operators have to process a huge amount of information, and the detection of future overloads is based on past experiences. Moreover, due to the inherent uncertainty of weather information, a reliable decision support framework is required to handle these situations as efficiently as possible. We propose a Deep Learning model able to extract the relationship between both the historical data and the implemented actions, accurately identifying the intervals of time that must be regulated. The proposed model achieves an accuracy between 80% and 90% across six traffic volumes belonging to both the MUAC and REIMS regions, a recall higher than 85%, and an F1-score higher than 0.8 in all the cases. Furthermore, the confidence-level analysis shows a really high activation when making a prediction. Finally, the SHapley Additive exPlanations method is applied to identify the most relevant input features. This work was funded EUROCONTROL under Ph.D. Research Contract No. 18-220569-C2 and by the Ministry of Economy, Industry, and Competitiveness of Spain under GrantNumber TRA2016-77012-R. Peer Reviewed