Unstructured pavement type identification method based on multi-source sensor information fusion

Abstract

The invention discloses an unstructured pavement type identification method based on multi-source sensor information fusion. The method comprises the following steps: step 1, establishing a multi-source sensor synchronous data acquisition platform; step 2, achieving space-time alignment of the pavement image data and the vehicle dynamics state data; 3, preprocessing the acquired image information;4, estimating the rolling resistance, the adhesion coefficient and the gradient parameter of the corresponding unstructured pavement; 5, obtaining another road surface type identification result, wherein the classifier is recorded as a second classifier; and step 6, fusing the road surface type results of the first classifier and the second classifier to obtain a final road surface type identification result. The method has the advantages that part of classification errors generated by only using single sensor information are corrected; road surface type identification is achieved; accordingto the spatial alignment mode of the road surface image data and the vehicle dynamics state data, errors are effectively reduced, and the spatial alignment precision is guaranteed.

Description

technical field [0001] The invention relates to an unstructured pavement type identification method, in particular to an unstructured pavement type identification method based on multi-source sensor information fusion. Background technique [0002] At present, a car is a means of transportation on the road, and its motion is the result of the interaction between the car and the road. The quality of the road surface will directly affect the operation of the vehicle. When smart cars drive on unstructured roads with no lane lines and clear road boundaries, or are affected by roadside trees or building projections and water marks, or the road surface itself is uneven and unstructured, it will be affected by the bumps and undulations of the road surface, causing The vertical vibration of the vehicle affects the ride comfort and passability of the vehicle. The perception of road conditions is an important part of automotive intelligent technology. Reliable real-time cognition te...

AI Technical Summary

Problems solved by technology

The former is sensitive to vehicle speed, light, shadows, etc., and will affect the recognition results when the road surface is covered by other objects; the latter is based on the characteristics of vehicle dynamics such as resistance, wheel speed fluctuations, acceleration fluctuations and other characteristics. Such methods only After driving for a certain distance on the unstructured road, the road surface type can be identified according to the accumulated characteristic signal, which has a certain hysteresis. It is likely that the unstructured road has already had an adverse effect on the vehicle during the identification process.

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