An Overview of Drone Energy Consumption Factors and Models

At present, there is a growing demand for drones with diverse capabilities that can be used in both civilian and military applications, and this topic is receiving increasing attention. When it comes to drone operations, the amount of energy they consume is a determining factor in their ability to achieve their full potential. According to this, it appears that it is necessary to identify the factors affecting the energy consumption of the unmanned air vehicle (UAV) during the mission process, as well as examine the general factors that influence the consumption of energy. This chapter aims to provide an overview of the current state of research in the area of UAV energy consumption and provide general categorizations of factors affecting UAV's energy consumption as well as an investigation of different energy models

Bike Share's Impact on COVID-19 Transmission and Bike Share's Responses to COVID-19: A case study of Washington DC

Due to the wide-ranging travel restrictions and lockdowns applied to limit the diffusion of the SARS-CoV2 virus, the coronavirus disease of 2019 (COVID-19) pandemic has had an immediate and significant effect on human mobility at the global, national, and local levels. At the local level, bike-sharing played a significant role in urban transport during the pandemic since riders could travel outdoors with reduced infection risk. However, based on different data resources, this non-motorized mode of transportation was still negatively affected by the pandemic (i.e., relative reduction in ridership). This study has two objectives: 1) to investigate the impact of the COVID-19 pandemic on the numbers and duration of trips conducted through a bike-sharing system -- the Capital Bikeshare in Washington, DC, USA; and 2) to explore whether land use and household income in the nation's capital influence the spatial variation of ridership during the pandemic. Towards realizing these objectives, this research looks at the relationship between bike sharing and COVID-19 transmission as a two-directional relationship rather than a one-directional causal relationship. Accordingly, this study models i) the impact of COVID-19 infection numbers and rates on the use of the Capital Bikeshare system and ii) the risk of COVID-19 transmission among individual bike-sharing users. In other words, we examine i) the cyclist's behavior as a function of the COVID-19 transmission evolution in an urban environment and ii) the possible relationship between the bike share usage and the COVID-19 transmission through adopting a probabilistic contagion model. The findings show the risk of using a bike-sharing system during the pandemic and whether bike sharing remains a healthier alternative mode of transportation in terms of infection risk

A Framework to Assess the Correlation between Transportation Infrastructure Access and Economics: Evidence from Iran

One of the most important impacts of access to transportation infrastructure is the economic and social well-being of residents. However, it is important to know, how much of an impact it has? Which of the access routes-road, rail, or air-has more impact? What methods can be used to assess this effect? Does this effect vary from country to country? This study attempts to provide a framework to examine the correlation between the access of a country’s cities (to various types of rail, air, and road transportation networks) and the economic and social parameters of its inhabitants. For this purpose, the connection of the city to the rail network was calculated by taking into account the distance in time between the city and the nearest station. A city’s road access is calculated by finding the average road distance of a city to other cities in that country. A city’s access to air traffic is calculated based on the weekly flights of that city’s airport (if that city has an airport). To evaluate the performance of the proposed framework, a case study is conducted in Iran. The results of the case study show that the access of cities to transportation networks strongly influences economic development and population size in Iran. Pearson’s correlation coefficients between transport infrastructure and economic growth and population size are 0.641 and 0.725, respectively. It was also found that among the transport networks, road transport is more correlated with economic development and unemployment rate of Iranian cities compared to other transport modes