Abstract
The accurate recognition of road condition is one of the important factors that influence vehicle safety performance. This paper comes up with an original mathematical method of an interval recognition algorithm of the pavement surface condition based on Lagrange interpolation. The ordinate of the peak point is solved by the Lagrange interpolation method, and the pavement surface condition is deduced by the interval identification algorithm. The simulation results from six typical roads and the varied pavement surface show that besides the cobblestone pavement which is not common in the daily road, the estimation error of the initial tire-road friction coefficient by the Lagrange interpolation method is less than 2%, the pavement surface condition can be identified by interval recognition algorithm quickly and accurately, and the response time is less than 0.2 seconds.
Highlights
In order to reduce the occurrence of traffic accidents, major automobile companies and research institutes began to research and develop vehicle active safety control technology, such as ABS, TCS, EBD, ESP, and ACC. e essence of these active control strategies is to adjust the force acting on the tire and pavement surface so as to achieve the purpose of braking control and vehicle stability control, which are restricted by the adhesion conditions between the tire and the pavement surface [1, 2]
Besides the quality of active safety control strategy, the significant automated driving depends to a great extent on whether the current road adhesion coefficient can be fully utilized
An original mathematical method of the interval recognition algorithm of road adhesion coefficient based on Lagrange interpolation is presented. e ordinate of the peak point of the road curve to be estimated is solved by the Lagrange interpolation method, and the pavement surface condition is deduced by the interval identification algorithm based on the recognition interval in which the ordinate value of “a0” located
Summary
In order to reduce the occurrence of traffic accidents, major automobile companies and research institutes began to research and develop vehicle active safety control technology, such as ABS, TCS, EBD, ESP, and ACC. e essence of these active control strategies is to adjust the force acting on the tire and pavement surface so as to achieve the purpose of braking (driving) control and vehicle stability control, which are restricted by the adhesion conditions between the tire and the pavement surface [1, 2]. E main advantage of the “cause-based” method is that it can identify the pavement surface condition before the vehicle passes, which is of great significance to future pilotless This method is not limited by the current road adhesion coefficient and can predict the maximum tireroad friction coefficient precisely under the condition that the friction between the tire roads is low. This method exists two main disadvantages: first, the experiment-based approach considers only the road level and not the tire wear of the vehicle itself.
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