面向自动驾驶编队的沥青路面结构疲劳寿命预估模型

Fatigue Life Prediction Model for Asphalt Pavement Structure Under Truck Platooning

与传统有人驾驶货车相比,自动驾驶货车编队具有更为紧凑的队列形式与更快的行驶速度,极大提高了道路通行能力与运输效率,但同时也使得车辆荷载作用特点发生了显著变化,从而影响沥青路面的疲劳寿命。针对现行疲劳寿命预估模型在自动驾驶货车编队行驶场景下适用性不足的问题,以编队荷载作用下的沥青路面结构层底应变波形特征为切入点,建立了面向自动驾驶货车编队的柔性基层沥青路面疲劳寿命预估模型。通过分析375种不同编队荷载工况下的沥青层层底应变波形,发现层底最大拉应变随行驶速度、前后车间距、左右车间距的增大而减小,随单列车辆数的减少而减小;针对波形参数的主成分分析结果表明,编队荷载下的应变波形可以用D、β_(D-)、θ_(1sμ)、θ_(2sμ)、ε_(n)共5个相互独立的特征参数进行表达,且该波形特征参数与编队行驶特性参数之间存在不同程度的相关性;依据等效损伤理论计算标准温度(20℃)下柔性基层沥青路面达到疲劳破坏时的编队荷载作用次数,进而提出了基于应变波形特征的沥青路面结构疲劳寿命预估模型。对比仿真结果与模型计算结果发现自动驾驶货车编队场景下该预估模型具有可靠性。总结来看,通过引入自动驾驶货车编队的行驶特性,揭示了应变波形特征和编队行驶特性对疲劳寿命的影响规律,形成了面向自动驾驶货车编队的应变波形特征提取方法,提出了该场景下的疲劳寿命预估模型,研究结果可为今后面向自动驾驶场景的沥青路面结构设计方法提供一定的理论指导。

Improving the capacity and efficiency of traffic flow is essential for road transport sector while,in which the truck platooning could play an important role in the near future.As a result,the complex load characteristics of truck platooning could be a problem for pavement design,and the existing fatigue performance model is not sufficiently sophisticated to capture the important influences arising from this scenario.A fatigue life prediction model for asphalt pavements was established by considering the characteristics of the bottom strain waveforms of the layer under a platooning load as the entry point.By analyzing the strain waveforms of the asphalt layer under 375 different loading conditions,it was shown that the maximum tensile strain at the bottom of the layer decreases with an increase in the driving speed,an increase in the distance between the front and rear axles,an increase in the distance in between the left and right axles,and a decrease in number of vehicles in the queue.The strain waveform feature can be predicted well using the five independent shape parameters of D,β_(D-)、θ_(1sμ)、θ_(2sμ)、ε_(n),which allows for a further determination of correlations between the truck platooning characteristics and the waveform features.Based on the linear damage accumulation theory,the number of load actions once a flexible base asphalt pavement exhibits fatigue damage at a standard temperature(20℃)is determined,and a fatigue life prediction model based on the strain waveform feature of the bottom layer is proposed.By comparing the simulation results with theoretical calculations,it was found that the model can effectively predict the fatigue life of asphalt pavements under an autonomous truck platooning scenario.In summary,this study introduced the driving characteristics of autonomous truck platoons and examined the influences of the pavement strain response waveform characteristics on pavement fatigue life.Based on these results,a strain waveform feature extraction method for an autonomous truck platooning scenario and a fatigue life prediction model including a temperature correction method are proposed.These achievements provide theoretical support for future asphalt pavement structural design methods for autonomous driving scenarios.