Aerodynamic optimization of a VTOL drone using winglets

Prieto, Marina; Escartí-Guillem, Mara S.; Hoyas, Sergio

doi:10.1016/j.rineng.2022.100855

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…Newer UAVs such as JOUAV CW series VTOL can last up to 480 min and can carry up to 20 kg payload. The price of professional VTOL drones is $3000-300,000 [65]. Depending on the available budget of the transport authority, specific products can be selected based on their requirements (i.e., average estimated flight time to reach the incident location).…”

Section: Imentioning

confidence: 99%

“…The issue of providing a clearway to an EV near the intersection is addressed using a 397 discrete-time model. This sort of model is used in bi-level optimization trajectory design 398 problems [65]. In this case, the higher level task will be used to clear the intersection for 399 an EV and the lower level task will be assigned to reduce the impact on non-emergency 400 vehicles.…”

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confidence: 99%

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IoT-Based Emergency Vehicle Services in Intelligent Transportation System

Chowdhury

Kaisar

Khoda

et al. 2023

Sensors

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Emergency Management System (EMS) is an important component of Intelligent transportation systems, and its primary objective is to send Emergency Vehicles (EVs) to the location of a reported incident. However, the increasing traffic in urban areas, especially during peak hours, results in the delayed arrival of EVs in many cases, which ultimately leads to higher fatality rates, increased property damage, and higher road congestion. Existing literature addressed this issue by giving higher priority to EVs while traveling to an incident place by changing traffic signals (e.g., making the signals green) on their travel path. A few works have also attempted to find the best route for an EV using traffic information (e.g., number of vehicles, flow rate, and clearance time) at the beginning of the journey. However, these works did not consider congestion or disruption faced by other non-emergency vehicles adjacent to the EV travel path. The selected travel paths are also static and do not consider changing traffic parameters while EVs are en route. To address these issues, this article proposes an Unmanned Aerial Vehicle (UAV) guided priority-based incident management system to assist EVs in obtaining a better clearance time in intersections and thus achieve a lower response time. The proposed model also considers disruption faced by other surrounding non-emergency vehicles adjacent to the EVs’ travel path and selects an optimal solution by controlling the traffic signal phase time to ensure that EVs can reach the incident place on time while causing minimal disruption to other on-road vehicles. Simulation results indicate that the proposed model achieves an 8% lower response time for EVs while the clearance time surrounding the incident place is improved by 12%.

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confidence: 99%

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confidence: 99%