Research on longitudinal collision avoidance control of commercial semi-trucks
To reduce the occurrences of rear-end accidents of commercial semi-trucks in hazardous situations like slippery roads on rainy days,this paper proposes a safe distance model based on real-time braking distance prediction(BDP)by employing the magic formula tire model and recursive least squares algorithm(RLS)to estimate the road adhesion coefficient and BP neural network for the prediction of the braking distance.The hierarchical collision avoidance control strategy is designed.The co-simulation of CCRb,CCRs and CCRm on high and low adhesion coefficient pavement is conducted to verify the effectiveness of the model.Our simulation results show the BDP and Mazda models effectively avoid collisions under three working conditions on the road surfaces with high adhesion coefficients.The BDP model achieves a shorter stopping distance at the end of braking,better in line with the driving habits and meeting the requirements for driving efficiency and comfort.On the road surfaces with low adhesion coefficients,the Mazda model only effectively avoids collisions in CCRm working conditions whereas the BDP model successfully shuns collisions in three working conditions.The BDP model effectively reduces the occurrences of rear-end accidents on pavements with low adhesion coefficients.
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