A vehicle-mounted drone

Abstract

The invention belongs to the technical field of transportation, and specifically relates to a vehicle-mounted unmanned aerial vehicle, including a camera, a data processing module, a GPS navigation module, an automatic flight control module and a wireless communication module. , the camera sends the collected video signal to the data processing module, and the data processing module converts the video signal into a relay signal that can be sent and received by the wireless communication module, and the wireless communication module remotely sends the relay signal to the vehicle terminal, and the vehicle terminal performs signal processing Process and display the video information collected by the drone on the vehicle's central control screen in real time. The present invention uses drones to collect video of road traffic within a certain range in front of the vehicle, and sends the video to the vehicle-mounted terminal in real time. The driver can clearly understand the traffic flow ahead through the vehicle's central control screen, so as to change lanes in advance to avoid congestion. Improved traffic efficiency.

Description

Technical field [0001] The invention belongs to the technical field of transportation, and specifically relates to a vehicle-mounted drone. Background technique [0002] With the continuous development of society and the gradual improvement of people’s living standards, cars have become an indispensable means of transportation for most families. However, as the number of cars continues to increase, urban traffic conditions have become increasingly busy. In some large and medium-sized cities, Traffic congestion in the morning and evening rush hours is even more commonplace, and for drivers, predicting the traffic on the road ahead can effectively avoid congestion. With the continuous development of network technology, electronic maps already have the function of road condition forecasting, but it is worth noting that the road condition forecasts of electronic maps are often calculated based on big data, so the forecast results may be different from the actual road conditions, for ...

AI Technical Summary

Problems solved by technology

With the continuous development of network technology, electronic maps already have the function of road condition forecasting, but it is worth noting that the road condition forecasts of electronic maps are often calculated based on big data, so there may be discrepancies between the forecast results and actual road conditions, for example , on a highway with multiple lanes, some lanes may be congested due to traffic accidents or traffic control, while some lanes may pass at a faster speed. In this case, the electronic map can only give the only forecast As a result, it is impossible to tell the driver which lane is smooth and which lane is more congested. After the vehicle enters the congested road, it is difficult to change lanes. Forcibly changing lanes will easily lead to new traffic accidents.

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