Introduction of autonomous and connected trucks (ACTs) is expected to result in drastic changes in operational characteristics of freight shipments, which may in turn have significant impacts on highway safety, vehicle fuel consumption, and infrastructure durability. One such important change is the formation of truck platoons which can be defined as the convoy of trucks travelling in a very close distance. Reducing congestion, regulating traffic, and improving fuel efficiency are some of reported and expected benefits of platooning. Yet such platooning operations may accelerate the damage accumulation within pavement structures because the lateral position of successive trucks within a lane is expected to be similar (i.e., channelized traffic) and the time between two consecutive axle loads (i.e., resting period) is expected to be reduced. Therefore, this study develops a platooning-control strategy for a fleet of ACTs such that the lateral position of trucks and spacing between them can be explicitly optimized to minimize damage to the pavement. Pavement damage is simulated using recently developed pavement performance models. On the other hand, fluid dynamics models were developed to compute fuel-cost due to aerodynamic drags. Three numerical optimization algorithms, genetic algorithms, particle swarm optimization and pattern search algorithm were used to solve the objective function. The proposed control strategy efficiency is demonstrated through a case study; relative costs to agencies and users could be reduced by 9%.

预计将引入自动驾驶卡车和互联卡车（ACT），这将导致货运操作特性发生巨大变化，进而可能对高速公路安全，车辆燃油消耗和基础设施耐久性产生重大影响。这样的重要变化之一是卡车排的形成，可以将其定义为非常近距离行驶的卡车车队。减少交通拥堵，调节交通量和提高燃油效率是排行的已报道和预期的好处。然而，这样的排行操作可能会加速路面结构内的损伤累积，因为预计车道内连续卡车的横向位置是相似的（即，通道化交通），并且两个连续车轴载荷之间的时间（即，静止期）预计会达到减少。因此，本研究为ACT车队开发了一种排控策略，以便可以明确优化卡车的侧向位置和卡车之间的间距，以最大程度地减少对路面的损坏。使用最近开发的路面性能模型模拟路面损坏。另一方面，开发了流体动力学模型来计算由于空气阻力引起的燃料成本。用三种数值优化算法，遗传算法，粒子群算法和模式搜索算法求解目标函数。案例研究证明了拟议的控制策略效率。代理商和用户的相对成本可以降低9％。这项研究为ACT车队开发了一种排控策略，以便可以明确优化卡车的侧向位置和卡车之间的间距，以最大程度地减少对路面的损坏。使用最近开发的路面性能模型模拟路面损坏。另一方面，开发了流体动力学模型来计算由于空气阻力引起的燃料成本。用三种数值优化算法，遗传算法，粒子群算法和模式搜索算法求解目标函数。案例研究证明了拟议的控制策略效率。代理商和用户的相对成本可以降低9％。这项研究为ACT车队开发了一种排控策略，以便可以明确优化卡车的侧向位置和卡车之间的间距，以最大程度地减少对路面的损坏。使用最近开发的路面性能模型模拟路面损坏。另一方面，开发了流体动力学模型来计算由于空气阻力引起的燃料成本。用三种数值优化算法，遗传算法，粒子群算法和模式搜索算法求解目标函数。案例研究证明了拟议的控制策略效率。代理商和用户的相对成本可以降低9％。开发了流体动力学模型来计算由于空气阻力引起的燃料成本。用三种数值优化算法，遗传算法，粒子群算法和模式搜索算法求解目标函数。案例研究证明了拟议的控制策略效率。代理商和用户的相对成本可以降低9％。开发了流体动力学模型来计算由于空气阻力引起的燃料成本。用三种数值优化算法，遗传算法，粒子群算法和模式搜索算法求解目标函数。案例研究证明了拟议的控制策略效率。代理商和用户的相对成本可以降低9％。