Massachusetts Institute of Technology (MIT) researchers have developed a mathematical model to study the effects of two different scheduling policies on fuel consumption and travel delays in order to determine the optimal deployment of trucks.
Under a timetable policy, vehicles assemble and depart as a platoon at set times, either at regular or staggered intervals. For feedback scheduling, vehicles leave as a platoon when a set number or varying numbers of trucks are assembled.
The MIT team found timetables set to deploy platoons at regular intervals were more efficient and cost-effective than those deployed at staggered times. Moreover, feedback scenarios that waited for the same number of trucks to assemble before deploying were better than scenarios that varied the number of trucks in a platoon. Overall, feedback policies saved about 5% more fuel than timetable scenarios.
The mathematical model depends on trucks following each other at very close range, which may be difficult for drivers to maintain over long distances. The researchers say truck platoons eventually may require autonomous driving systems to activate during long stretches to keep the platoon close enough to save fuel.
From MIT News
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