A method for estimating the safety distance based on the peak adhesion coefficient of the road ahead

Abstract

The invention discloses a safe distance estimation method based on a front pavement peak attachment coefficient, and belongs to the technical field of the driving safety. The method comprises the following steps: extracting image characteristics by collecting a typical road image, and computing a pavement utilization attachment coefficient and a real-time slippage rate s according to the collectedcurrent vehicle driving state parameter, thereby computing an actual peak attachment coefficient mu-max; and obtaining the peak attachment coefficient mu-imax of the front pavement by designing and training a HMM model, and taking the peak attachment coefficient mu-imax as an influence factor of a safe distance model, thereby estimating safe distance conforming to the actual pavement status. Thehidden front pavement peak attachment coefficient which cannon be directly observed can be predicted in real time, the proposed improved safe distance model considers the influence on the vehicle by the pavement status, the safe distance conforming to the actual pavement condition can be computed more accurately, and the occurrence of the rear-end collision and like traffic accidents under wickedattachment condition is reduced.

Description

technical field [0001] The invention belongs to the technical field of driving safety, and in particular relates to a safety distance estimation method based on the peak adhesion coefficient of the road ahead. Background technique [0002] With the rapid increase of car ownership in recent years, road traffic safety issues have become the focus of social attention. People's requirements for safety performance in the process of driving are constantly increasing. More and more cars are equipped with active safety control systems to assist drivers in reasonably controlling the safe distance between cars. Changes in the road surface will directly affect the safe distance of the car. The peak adhesion coefficient can be used to characterize the change of road surface conditions, but due to the influence of road surface characteristics and other aspects, its value is not unique even under the same typical road surface type. Therefore, the accurate estimation of the road surface pe...

AI Technical Summary

Problems solved by technology

[0003] At present, scholars at home and abroad have done a lot of research on the above problems. The identification of road conditions is mainly divided into the following two categories: one is to use sensors to directly measure the parameters of the road surface, but the sensor can only detect the type and dryness of the road ahead. Judging wet conditions, it is difficult to estimate the adhesion coefficient of the road ahead in real time

The second type is indirect estimation through the response of vehicle dynamic parameters. However, due to the influence of factors such as occlusion and human cleaning, the adhesion characteristics of the current road surface are significantly different from those of the road ahead, and it is impossible to estimate the degree of danger of the sudden change of road surface. This leads to a large error in the prediction of the safe distance of the vehicle, which is likely to cause traffic accidents or affect the traffic capacity of the road

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