The COVID-19 pandemic that erupted in early 2020 has affected the everyday life, the practices, and the perceptions of the global population significantly. The aim of this paper is to investigate the perceptions, experiences, and practices of the active population regarding everyday urban life (working conditions, mobility, urban space, etc.) in the context of the first wave of the pandemic, by focusing on people who live and work in Greek cities. The data were collected using a structured questionnaire addressed to an active population. The majority of respondents declared that their personal and family lives were affected by the lockdown, with significant effects on their professional life and economic activities. Stress and fear were two feelings that increased. As far as mobility was concerned, the majority of respondents were unwilling to change their commuting practices. Although most of our findings presented a homogenous distribution in our sample, some changes in perceptions, experiences, and practices were correlated with the gender, age, and family status of the respondents. The results of the analysis provide useful information to policy makers and show that it is necessary to radically rethink aspects of urban space and urban mobility, in relation to the multiple problems and dynamics of the active population.

Low-carbon transport is a priority in addressing climate change. Transport is still almost totally dependent on fossil fuels (96%) and accounts for almost 60% of global oil use. Sustainable transport systems, both passenger and freight, should be economically and technically feasible, but also low-carbon and environmentally friendly. The calculation of greenhouse gas emissions in transport projects is becoming a primary target of transport companies as a part of an endeavor for low-carbon strategies to reduce the energy demand and environmental impact. This paper investigates the CO₂ impact of construction and operation of the main highway and railway line infrastructure in Greece, which connects Athens and Thessaloniki, the capital and the second biggest city in Greece respectively and provides a comparative analysis in roadway and railway transport.

Drivers play a significant role in causing serious accidents, which underscores the need for further investigating the human element in order to improve road safety. Given the predominance of the information processing approach in driver’s behavior research field, an important psychological construct, Mental Workload (MWL), has been introduced to study the behavior of drivers. The objective of this paper is to investigate the impact of increased MWL on driver behavior and specifically the changes in driver’s Reaction Time (RT) under increased MWL. The experiment conducted in the driving simulator of the Hellenic Institute of Transport which is part of the Centre for Research and Technology Hellas, with the participation of 56 subjects from all age groups. For the simulation of the increased MWL conditions during driving, a secondary task was employed. To this end, the MIT AgeLab Delayed Digit Recall Task in the 1-back version was adapted for the needs of the present research. The driving scenario included 4 unexpected events, which further increase driver’s MWL. Driving performance was observed and relative parameters were measured as RT on the unexpected events, accidents occurred, and maneuvers performed. Appropriate statistical analysis was performed to examine the difference in the drivers’ RT in the unexpected events. Results demonstrated that higher MWL increased drivers’ RT in the majority of the participants. Furthermore, results also indicated a number of participants that probably employed adaptive control behaviors to counterbalance the increased MWL. Overall, variance on MWL proved to play an important role on driver performance, and thus further research on its consequences on driving performance, and the factors that influence its variance during driving, is imperative.

Research into collecting and measuring reliable, accurate, and naturalistic microscopic traffic data is a fundamental aspect in road network planning scientific literature. The vehicle trajectory is one of the main variables in traffic flow theory that allows to extract information regarding microscopic traffic flow characteristics. Several methods and techniques have been applied regarding the acquisition of vehicle trajectory. The forthcoming applications of intelligent transport systems on vehicles and infrastructure require sufficient and innovative tools to calibrate existing models on more complex situations. Unmanned aerial vehicles (UAVs) are one of the most emerging technologies being used recently in the transportation field to monitor and analyze the traffic flow. The aim of this paper is to examine the use of UAVs as a tool for microscopic traffic data collection and analysis. A comprehensive guiding framework for accurate and cost-effective naturalistic traffic surveys and analysis using UAVs is proposed and presented in detail. Field experiments of acquiring vehicle trajectories on two multilane roundabouts were carried out following the proposed framework. Results of the experiment indicate the usefulness of the UAVs technology on various traffic analysis studies. The results of this study provide a practical guide regarding vehicle trajectory acquirement using UAVs.

Despite the significant progress in the last few decades, road safety improvement still constitutes an imperative global need. Especially in urban areas, the improvement of road safety is an even more complicated and multi-factor problem. Every minute, a human life is lost in an urban road network in the world. Given that almost all road accidents are preventable, more effective planning toward improving road safety, as a structural element of sustainable urban mobility, is imperative. The aim of the present research is to provide decision support analysts and policy-makers with a decision-support tool that identifies and prioritizes the factors undermining road safety in an urban area, with a view to developing effective policies. For this purpose, a comprehensive inventory of factors that may undermine road safety in an urban area, as well as an inventory of relevant measures and policies, is provided, based on an international literature review. The most important factors and, subsequently, the most effective measures and policies are identified and prioritized through a multi-criteria approach (modified Delphi–analytical hierarchy process (AHP)–technique for order preference by similarity to ideal solution (TOPSIS)). The Greek urban road networks, starting from the second largest city in Greece (Thessaloniki), are selected as a case study. Problems related to limited resources not allowing for systematic surveillance and policing, making arbitrary decisions instead of adopting a scientific decision-aiding methodology, education and mentality issues, infrastructure planning and maintenance, cooperation and coordination between different authorities, and laxity of penalties are highlighted as the most important factors, based on which four sets of measures and policies are identified and prioritized.