Coordination of cross-carrier truck platooning
Abstract: The need for sustainable transportation solutions is urgent as the demand for mobility of goods and people is expected to multiply in the upcoming decades. One promising solution is truck platooning, which shows great potential in reducing the energy consumption and operational costs of trucks. To utilize the benefits of truck platooning to the fullest, trucks with different schedules and routes in a road network need coordination to form platoons. This thesis addresses platoon coordination when trucks can wait at hubs to form platoons. We assume there is a reward for driving in a platoon and a cost for waiting at a hub, and the objective is to maximize the overall profit. We focus on coordinating trucks from different carriers, which is important considering that many platoon opportunities are lost if only trucks from the same carrier form platoons.In the first contributions of the thesis, we propose coordination solutions where carriers aim to maximize their own profits through cross-carrier platoon cooperation. We propose an architecture of a platoon-hailing service that stores reported platooning plans of carriers and, based on these, informs carriers about the platoons their trucks can join when they make platooning decisions. A realistic simulation study shows that the cross-carrier platooning system can achieve energy savings of 3.0% and 5.4% when 20% and 100% of the trucks are coordinated, respectively. A non-cooperative game is then formulated to model the strategic interaction among trucks with individual objectives when they coordinate for platooning and make decisions at the beginning of their journeys. The existence of at least one Nash equilibrium is shown. In the case of stochastic travel times, feedback-based solutions are developed wherein trucks repeatedly update their equilibrium decisions. A simulation study with stochastic travel times shows that the feedback-based solutions achieve platooning rates only $5\%$ lower than a solution where the travel times are known. We also explore Pareto-improving coordination guaranteeing each carrier is better off coopering with others, and models for distributing the profit within platoons.In the last contributions of the thesis, we study the problem of optimally releasing trucks at hubs when arriving according to a stochastic process, and a priori information about truck arrivals is inaccessible; this may be sensitive information to share with others. First, we study the release problem at hubs in a hub-corridor where the objective is to maximize the profit over time. The optimality of threshold-based release policies is shown under the assumption that arrivals are independent or that arrivals are dependent due to the releasing behavior at the preceding hub in the corridor. Then, we study the release problem at a single hub where the aim is to maximize the profit of trucks currently at the hub. This is realistic if trucks are only willing to wait at the hub if they can increase their own profits. Stopping time theory is used to show the optimality of a threshold-based release policy when arrivals are independent and identically distributed. These contributions show that simple coordination approaches can achieve high profits from platooning, even under limited information.
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