Maximizing Truck Platooning Participation with a Focus on Privacy and Preference-Based Matching

Truck platooning refers to a group of trucks driving closely together, using advanced connected and automated driving technologies to reduce energy consumption, operating costs, and emissions. Additionally, platooning can optimize road space utilization, increase road capacity, and improve traffic safety. However, for platooning to be widely adopted, it is critical to attract as many trucks as possible to participate. The main obstacles to widespread platooning are a focus on the system's optimal outcome rather than individual utility, privacy concerns, and the challenge of matching trucks for platooning. To address these issues, this research proposes a preference-based truck matching system that considers the stability of platoons, which is influenced by truck preferences for platooning partners. This approach is scientifically intriguing and practical for the highly fragmented US trucking sector, where preferences for fuel savings and schedule coordination affect platoon formation. To safeguard trucks' information privacy, the research suggests a platoon matching system that enables each truck to encrypt its itinerary information before sending it to a two-cloud system that protects data and facilitates secure and private platoon formation. Furthermore, the research proposes a platform that can consider multiple route options from a truck to find platoon partners, increasing the likelihood of forming a platoon, especially when the number of participating trucks is low. The proposed systems are computationally efficient, scalable, and effective in increasing fuel savings.