Unmanned vehicle intelligent decision-making method based on motivation and risk assessment

Abstract

The invention discloses an unmanned vehicle intelligent decision-making method based on motivation and risk assessment. The method comprises the following steps: firstly, surrounding environment conditions and motivation are analyzed when a vehicle needs to be subjected to state change in a high-speed environment; on the basis, the motivation for changing the driving state is extracted and servesas the core of behavior decision making, decision making is conducted only when the motivation is triggered, and the current driving state is still kept under other conditions. And meanwhile, an unmanned vehicle surrounding environment risk assessment model is established to dynamically verify the decision result, the decision rationality is judged, and the optimal decision target point is calculated. According to the method, excessive meaningless decisions of a decision-making system in the driving process of the driverless automobile can be avoided, the calculation efficiency is improved, and real-time, efficient and safe driving decisions of the driverless automobile in a dynamic uncertain environment are realized.

Description

technical field [0001] The invention relates to the technical field of unmanned vehicle decision-making, in particular to an intelligent decision-making method for unmanned vehicles based on motivation and risk assessment. Background technique [0002] With the rapid development of computer and communication technology, self-driving cars have gained more and more attention. Major auto companies around the world are also stepping up research and development of higher-level technologies for autonomous driving. Advanced auxiliary technologies and decision-making algorithms such as BSD, CTA, IACC, etc. developed to cope with different scenarios have been put into the market one after another. Among them, behavior decision-making and planning in the face of various traffic environments and emergency situations is the core technology to ensure safe and efficient driving of vehicles. At present, driving behavior decision-making is mainly based on rule-based or learning algorithm-...

AI Technical Summary

Problems solved by technology

When the actual human driver is driving, he does not plan all the feasible trajectories in his mind at all times, which greatly reduces the calculation efficiency and real-time performance.

Images