Intelligent connected vehicle corner danger warning system and method

Abstract

The invention provides an intelligent connected vehicle corner danger warning method. The method comprises a step of establishing a vehicle aerodynamic model and a three-degree-of-freedom vehicle torque balance equation, further deriving a centrifugal force expression when a vehicle passes a corner, and then jointly calculating a threshold speed of vehicle rollover, a step of extracting state parameters related to the vehicle rollover, establishing a limit state equation of the vehicle rollover, optimizing the solution process of the limit state equation by a first-order quadratic matrix method in the reliability theory and obtaining a performance function, a step of establishing a vehicle rollover state prediction model through a checkpoint method, obtaining a vehicle rollover state indexand thus calculating the probability of vehicle driving safety, and a step of determining whether to carry out vehicle hazard warning or not according to the probability of vehicle driving safety. According to the method, the danger of a forward corner can be predicted in advance, the risk indicators of vehicle cornering risks caused by various vehicles, roads and environments are comprehensivelyanalyzed, quantitative prediction indicators are provided in real time, and the stability and safety of the vehicle in driving in a corner are ensured.

Description

technical field [0001] The invention belongs to the technical field of intelligent networked vehicles, and in particular relates to an intelligent networked vehicle curve danger warning system and method. Background technique [0002] As the number of motor vehicles in my country increases year by year, the number of traffic accidents that occur each year also increases. According to statistics, the number of deaths caused by traffic accidents on bends in my country accounts for about 16.3%. Vehicles are prone to dangerous accidents such as vehicle collisions, sideslips, and rollovers on curves. Today's research on vehicle curve danger warning mainly focuses on the prediction of rollover time, vehicle roll angle threshold, vehicle lateral load transfer rate, and vehicle curve safety speed prediction, all of which are based on the analysis of vehicle dynamics and driver input. However, in reality, the cause of vehicle curve danger is not limited to the vehicle itself, but al...

AI Technical Summary

Problems solved by technology

For example, Chinese patent application CN106945670A discloses a vehicle anti-rollover system and control strategy based on driver input prediction, which only considers the human input factor, that is, the steering wheel angle, and proposes predictable vehicle rollover indicators without taking into account the environmental road and vehicle parameters

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