The invention relates to the technical field of
new energy vehicles, and discloses a cross-layer collaborative architecture-based vehicle
intelligent network connection test
system, which comprises the following steps of: establishing a tunnel longitudinal position
system taking a semi-closed tunnel door opening
reference surface as a space starting point, and mapping multi-source acquisition data to the tunnel longitudinal position
system to construct a cross-layer state
data set; extracting interference values such as
enclosure surface reflection, illumination transition, positioning attenuation and communication attenuation according to the set, fusing to generate a composite
distortion density, and calculating an interval midpoint and width of a preposed contraction high-risk interval according to the composite
distortion density; maximizing the response change rate of the vehicle
application layer in the high-risk interval by adopting a
particle swarm algorithm so as to obtain an
optimal test control
instruction set; executing a test based on the
instruction set, and remapping each layer of data to an interference synchronization coordinate system; and finally, calculating a trigger concentration point and a
distortion concentration point of an
application layer, quantifying a trigger offset to determine a core failure reason, and solidifying the core failure reason into a test template and an execution script.