Unmanned vehicle control method based on over-the-horizon synergetic cognition and unmanned vehicle control system based on over-the-horizon synergetic cognition

Abstract

The invention discloses an unmanned vehicle control method based on over-the-horizon synergetic cognition and an unmanned vehicle control system based on over-the-horizon synergetic cognition, and belongs to the field of intelligent traffic. The control system comprises an unmanned vehicle and an unmanned driving network supporting platform. The unmanned vehicle comprises an individual situation cognition system and a driving decision generation system. The unmanned driving network supporting platform comprises a global situation cognition system, a local situation cognition system and a driving decision generation system. The control method applying the control system comprises the steps that firstly the individual situation cognition system forms micro driving situation cognition; then the driving decision generation system receives information and processes the information and then issues the information to the driving decision generation system, and the driving decision generationsystem generates the final driving operation; and finally the unmanned vehicle receives and performs the final driving operation through the driving actuator. Real-time cognition of the traffic environmental situation is performed on the network terminal so that safe, efficient and reliable unmanned driving can be realized and the operability and the effectiveness of the unmanned vehicle controlsservice can be enhanced.

Description

technical field [0001] The invention belongs to the field of intelligent transportation, in particular to an unmanned vehicle control method and system based on beyond-the-horizon collaborative cognition. Background technique [0002] The Intelligent Traffic System (ITS for short) is the effective integration and application of advanced computer technology, data communication technology, sensor technology, electronic control technology, operations research and artificial intelligence in the entire transportation management system, strengthening the vehicle, road In order to establish a real-time, accurate and efficient comprehensive transportation management system that plays a role in a wide range and in all directions. Intelligent roads and safety assisted driving are one of the user service areas in the ITS system. Through ITS subsystems such as vehicle control, traffic monitoring, and operating vehicle management, artificial intelligence, big data, machine learning and o...

AI Technical Summary

Problems solved by technology

Through this method, unmanned vehicles can safely and reliably drive to the destination based on the OD point, but the lack of driving efficiency increases the pressure on the road network to a certain extent, and even aggravates traffic congestion and environmental pollution.

Because of the sensor system carried by the vehicle itself, the existing driverless cars are generally equipped with cameras, lidar, millimeter-wave radar, GPS, OBD, high-precision maps and inertial navigation, etc., and can only sense the traffic environment around the vehicle. For example, the effective maximum detection distance of an expensive 64-line laser radar is 150m, and the effective viewing distance of a general camera is only 5m-50m, that is, the vehicle can only perceive the traffic conditions within its visual range

When the driverless car is driving in a congested road or a complex and changeable road network environment, the driverless car will not be able to perceive more specific traffic conditions due to the obstruction of objects in the road environment.

Therefore, even if the traffic conditions on the future driving section beyond the visual range are good, the driverless car will not be able to drive efficiently because it has not planned the driving action rules in advance and is currently in a small section of road congestion, or it is beyond the visual range. The future driving section is also in a congested state, and the driverless car cannot perceive the road traffic state to be passed in the future, resulting in the vehicle being in a congested state at an unknown time due to the inability to make decisions

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