With the exponential growth of numerous drone operations ranging from infrastructure monitoring to even package delivery services, the integration of UAS in the smart city transportation systems is an actual task that requires radically new, sustainable (safe, secure, with minimum environmental impact and life cycle cost) solutions. The primary objective of this proposed option is the definition of routes as desired and commanded trajectories and their autonomous execution. The airspace structure and fixed routes are given in the global GPS reference system with supporting GIS mapping. The concept application requires a series of further studies and solutions as drone trajectory (or corridor) following by an autonomous trajectory tracking control system, coupled with autonomous conflict detection, resolution, safe drone following, and formation flight options. The second part of the paper introduces such possible models and shows some results of their verification tests. Drones will be connected with the agency, designed trajectories to support them with factual information on trajectories and corridors. While the agency will use trajectory elements to design fixed or desired trajectories, drones may use the conventional GPS, infrared, acoustic, and visual sensors for positioning and advanced navigation. The accuracy can be improved by unique markers integrated into the infrastructure.

Smart mobility and transportation, in general, are significant elements of smart cities, which account for more than 25% of the total energy consumption related to smart cities. Smart transportation has seven essential sections: leisure, private, public, business, freight, product distribution, and special transport. From the management point of view, transportation can be classified as passive or non-cooperating, semi-active or simple cooperating, active or cooperating, contract-based, and priority transportation. This approach can be applied to public transport and even to passengers of public transport. The transportation system can be widely observed, analyzed, and managed using an extensive distribution network of sensors and actuators integrated into an Internet of Things (IoT) system. The paper briefly discusses the benefits that the IoT can offer for smart city transportation management. It deals with the use of a hierarchical approach to total transportation management, namely, defines the concept, methodology, and required sub-model developments, which describes the total system optimization problems; gives the possible system and methodology of the total transportation management; and demonstrates the required sub-model developments by examples of car-following models, formation motion, obstacle avoidances, and the total management system implementation. It also introduces a preliminary evaluation of the proposed concept relative to the existing systems.

Impact assessment, in general, includes the environmental safety and security considerations, and cost/cost-benefit analysis of the used sources. As usual, the impact is evaluated at two levels: (1) impact during operation (usage) related to a chosen operational unit (e.g., running distance [km], operational time [h] or calendar time [h]), (2) the life-cycle (project life-cycle) impact. The environmental impact is characterized by the chemical and noise emissions. Safety and security are estimated by risks. Costs are calculated based on the required financial support and caused losses. All these calculations are related to the individual vehicles or vehicles with average behaviours. The investigation of sustainability impact requires a wider evaluation and approach, for example, by also including production and recycling beside the operational aspects. This paper generalizes the impact analysis. At first, it considers all types of impacts including the direct (e.g., accidents) and indirect long-term effects (e.g., health problems caused by emissions). All the impacts are expressed as costs. The defined Sustainable Transportation Performance Index (STPI) is the Total Life-Cycle Cost (TLCC) related to the unit of transport work. As such, it combines the life-cycle emissions evaluation and transport costing methods. It contains the total operational and total impact costs. The proposed approach introduces three new specific features in the impact analysis: (1) the impact is evaluated on the transportation system level, (2) the impact is estimated as the total value (including all the related sub-systems and elements, like vehicles, transport infrastructure, transport flow control, etc.), (3) proposes a unique index to describe the total impact. The paper describes the general equations and the developed methodology for the estimation of the total impact and analyses its applicability. The preliminary results demonstrate the applicability of the defined index and its evaluation methodology. It also shows the limitations of traditional cost models. Further test results and wider application of the methodology will be provided in a series of follow up papers by the research team.

Due to the introduction of highly automated vehicles and systems, the tasks of operators (drivers, pilots, air traffic controllers, production process managers) are in transition from “active control” to “passive monitoring” and “supervising”. As a result of this transition, the roles of task load and workload are decreasing while the role of the mental load is increasing, thereby the new type of loads might be defined as information load and communication load. This paper deals with operators’ load monitoring and management in highly automated systems. This research (i) introduces the changes in the role of operators and requirements in load management, (ii) defines the operators’ models, (iii) describes the possible application of sensors and their integration into the working environment of operators, and (iv) develops the load observation and management concept. There are some examples of analyses of measurements and the concept of validation is discussed. This paper mainly deals with operators, particularly pilots and air traffic controllers (ATCOs).

NextGen, SESAR, and other international projects intend to develop the coming air traffic management (ATM) environment to cope with the present problems, including e.g. capacity, efficiency, safety, and environmental impact. These projects also introduce considerable changes in the role of air traffic controllers (ATCOs), and shift some of the present tasks from ground to on-board (pilots) and diversify automation. Due to the consequential effects of these developments, (i) the models describing the present operational circumstances, (ii) the working conditions, and (iii) the working environment (e.g. human–machine interactions, task-work and mental loads, cognitive aspects, situation awareness, decision support) must be reconsidered and adapted to the future role of operators. This paper aims to describe a new approach to model the ATCOs’ working processes, and also introduces a new concept for the ATCOs’ future working environment. The developed model covers the situation awareness and decision making processes, including the subjective aspects of the ATCOs decision making based on their workload, mental condition, knowledge, or practice. The proposed new working environment contains special information displays, the decision support system and the ATCOs workload and mental condition measurement / monitoring system, based on objective, on-line, continuous, and nonintrusive measurement techniques. Some of the core systems developed in collaboration with HungaroControl were exhibited at the World ATM congress in 2014 and 2015.