Increasing use of Unmanned Aerial Vehicle (UAV) in urban environments poses to an increased risk of fallen UAVs impacting people and vehicles on the ground, as well as colliding with manned aircraft in the vicinity of airports. Risk management of UAV flights for safe operations is essential. We proposed a comprehensive risk assessment model for UAV operation in urban environments. Three risk categories (people, vehicles, and manned aircraft) were considered and each risk cost was quantified using collision probability. We adjusted the risk costs in various magnitudes to a same scale and conducted a sensitivity analysis to determine the optimal coefficients of the three risk cost models. We then computed the total risk and generated a risk cost map for path planning. Modified path planning algorithms were used to produce a cost-effective path, and we compared their performances in terms of total risk cost and computational time. Lastly, we performed simulations to validate the feasibility and effectiveness of our proposed risk assessment model. The results show that the risk-cost-based path planning method can generate safer path for UAV operations than the traditional shortest-distance-based method. Our proposed model can be extended to complex urban environments by including more relevant parameters and data. INDEX TERMS Unmanned aerial vehicle, risk assessment model, risk cost map, path planning, urban environments Fuqing Dai holds the Dean's Chair in Air Traffic Management School at the Civil Aviation University of China. He is also a professor focusing on the research of airspace planning and management, flight procedures design and optimization, UTM and ATM systems. Professor Dai obtained his master's degree from Ecole Nationale de l'Aviation Civile, France and bachelor's degree from Nanjing University, China.

No abstract

No abstract

As a hub airport, the aircraft should arrive at more airports, so the passengers will not change another aircraft to their destinations. But due to the limited time in one day, one aircraft only get few flight missions. At present scheduled flights are arranged between two airports as a pair of flights. This paper researched that when it is known the amount of destination airports how to arrange scheduled flights. This paper proposed a novel and innovative method that three aircrafts should arrive at fifteen airports and the total distance must be minimum data. After a comparative analysis of various heuristic algorithms, this paper choose ant colony algorithm as the research algorithm to solve this problem. After verify the validity of improved algorithm with the help of computer, this paper calculate the result of given data. The outcome indicates the improved ant colony algorithm was of great value.

No abstract