Intelligent air-ground vehicle and risk map construction method and device and air route planning method and device thereof

Abstract

The invention discloses an intelligent air-ground vehicle and a risk map construction method and device and an air route planning method and device thereof. The risk map construction method comprises the following steps: marking a no-fly area in a rasterized vehicle flight area map; then, sequentially determining the self failure falling probability Pinv of the carrier in each grid, the probability Pimp that the carrier collides with a pedestrian on the ground after falling and the lethal probability Pfat after the pedestrian is collided, and obtaining the total pedestrian casualty probability P of the carrier; and according to the ranking of the total casualty probability P, obtaining the risk map. The method can be used for establishing a stable and reliable flight safety guarantee system of the intelligent air-ground vehicle.

Description

technical field [0001] The invention belongs to the technical field of intelligent space-ground fusion vehicles. Background technique [0002] With the rapid development of the urban economy, the urban traffic is becoming increasingly saturated, the traffic efficiency is low, the comfort experience is poor, the road resources are tight, and the transportation system of the whole city is uncoordinated and lacks vitality. The new convenient, comfortable, economical and efficient The needs of the transportation system are becoming more and more urgent. [0003] An intelligent air-ground fusion vehicle that coordinates urban airspace and ground resources for intelligent air-ground transportation, that is, an intelligent air-ground vehicle can realize the effective docking of traditional cars and aircraft, road network resources and airspace resources, and is equipped with ground road network driving and low-altitude flight, etc. The function can promote the improvement of urban...

AI Technical Summary

Problems solved by technology

[0004] However, there are still a lot of problems in its specific implementation. For example, in traditional flight, the flight route focuses on whether the travel time and path length are optimal, and basically does not consider the cost of threats to ground personnel in different regions. Focus on design, but when flying in urban airspace, once a crash occurs, it will cause great harm to ground personnel. Therefore, it is necessary to establish a stable and reliable security system based on risk division for intelligent air-ground vehicles

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