Pigeon-flock-imitating intelligent vehicle formation cooperative adaptive cruise control switching method

Abstract

The invention discloses a pigeon-flock-imitating intelligent vehicle formation cooperative adaptive cruise control switching method. The method comprises the steps that firstly, each individual vehicle calculates a road congestion degree according to the number of obstacle vehicles within a perceptible range of the individual vehicle, and if the congestion degree delta i calculated by all the individual vehicles is larger than a congestion degree threshold value delta max, a motorcade enters a hierarchical control mode modeh; otherwise, the motorcade enters an equal interaction mode modee; then, in a current state, each individual vehicle i in the motorcade marks a neighbor vehicle j within a distance with relatively low communication delay so as to obtain a neighbor vehicle set, then control input is performed, the control input includes a formation control gain, a target point control gain and a following control gain, and the formation control gain, the target point control gain andthe following control gain are all added into a potential field function so as to maintain a function value within a reasonable range; and finally, safety is judged, each individual vehicle judges whether a direction of a control input vector is within the range of the obstacle angle theta avoi or not by calculating obstacle angles occupied by all obstacle vehicles within the perceptible range, and safety of a driving behavior is predicted.

Description

technical field [0001] The invention belongs to the field of formation control of intelligent vehicles, and in particular relates to a method for switching intelligent vehicle formation cooperative adaptive cruise control imitating a pigeon flock. Background technique [0002] With the advancement of science and technology and the increase of human needs, more and more smart cars have entered people's field of vision. At present, the collaborative control technology of intelligent vehicle fleet has become a major topic in this field. In 1986, the University of California, Berkeley established the PATH (Partners for Advanced Transit and Highways) institution, which stimulated an upsurge in the research work of fleet cooperative control. In 2011 and 2016, Europe has held two Cooperative Driving Challenge (Grand Cooperative Driving Challenge, GCDC), aiming to promote the development of Cooperative Adaptive Cruise Control (CACC) and alleviate the current world traffic problems....

AI Technical Summary

Problems solved by technology

The longitudinal cooperative control aims to improve the efficiency and safety of vehicle formation adaptive cruise. However, due to the extremely complex road conditions in the real environment and the high difficulty of cluster formation control, there is no mature and perfect fleet cooperative adaptive control strategy.

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