Maximizing Truck Platooning Participation with Preferences, Inclusion, and Privacy Preservation

该项目将创造新的方法来最大限度地提高卡车在排队中的参与度，排队指的是卡车成组行驶，卡车之间的间隔较小，以减少空气动力阻力。近年来，卡车运输部门一直在大力投资于排成一排的技术，主要是受到卡车能源使用减少的显著好处的推动。这个项目将调查促进广泛的卡车排队的根本问题，同时考虑到1)鉴于美国卡车运输部门的高度碎片化，个人卡车偏好；2)将不同来源、目的地和计划出发时间的卡车纳入成排；以及3)保护卡车信息隐私。这项研究的结果将与该行业合作产生，将有助于在美国实施卡车排队，以获得最大利益。这项研究也与社会对个人成员福祉、包容性、隐私和网络安全的日益重视相一致。通过系统的教育和推广工作，不同的学生群体将接触到卡车排成一排和技术支持的智能移动性的主题。该项目的目标是在考虑卡车偏好、包容性和隐私保护的情况下，为最大限度地提高卡车排成一排的参与度奠定理论基础。首先设计了卡车和排成排平台之间的交互过程，以便于为每辆卡车构建排成排伙伴的偏好列表。然后，研究了排队参与度最大化的两种方法：一种是稳定地将卡车划分成循环偏好的各方；另一种是求助于整数规划，探索极值点的半完整性，以寻求有效的求解方法。进一步制定了多种包容措施，并将其融入到排队参与最大化中。为了在寻求排队机会的同时保护隐私，构思并研究了一种用于构建卡车偏好列表的加密计算设计。该设计的核心是具有密钥分割、密文重新加密和利用所选密码系统的可加性同态性质的混淆的双云体系结构。将构建基于真实世界货运数据的卡车流量分解，并用于测试和评估不同地理尺度上的不同研究组成部分。该项目的结果不仅将有助于丰富卡车排队文献，还将为其他几个具有操作相似性的新兴移动系统提供见解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project will create novel approaches to maximizing participation of trucks in platooning, which refers to trucks traveling in groups with small inter-truck separation to reduce aerodynamic drag. The trucking sector has been heavily investing in platooning technologies in recent years, driven primarily by the significant benefits of truck energy use reduction. This project will investigate the fundamental issue of promoting widespread truck platooning while accounting for 1) individual truck preferences, given the high fragmentation of the US trucking sector; 2) inclusion of trucks of different origins, destinations, and planned departure time in forming platoons; and 3) preservation of truck information privacy. Results from the research, which will be produced in collaboration with the industry, will help inform truck platooning implementation in the US toward reaping the maximum benefits. The research also aligns with the growing societal emphasis on individual member well-being, inclusiveness, privacy, and cybersecurity. Diverse student groups will be exposed to the subject of truck platooning and technology-empowered smart mobility in general through systematic education and outreach efforts. The goal of this project is to establish a theoretical foundation for maximizing truck platooning participation taking into consideration truck preferences, inclusion, and privacy preservation. An interactive process between trucks and a platooning platform is first devised to facilitate construction of the preference list of platooning partners for each truck. The research then investigates two approaches for platooning participation maximization: one centers on stably partitioning trucks into parties of cycled preferences; the other resorts to integer programming with exploration of half-integrality of the extreme points for efficient solution methods. Multiple inclusion measures are further developed and integrated into the platooning participation maximization. To preserve privacy while seeking platooning opportunities, an encrypted computing design is conceived and examined for constructing truck preference lists. The core of the design is a two-cloud architecture with secret key splitting, ciphertext re-encryption, and obfuscation which leverages the additive homomorphic property of the chosen cryptosystem. Disaggregate truck flows based on real-world freight data will be constructed and used to test and evaluate the different research components at varying geographical scales. The results from this project will not only contribute to enriching the truck platooning literature but lend insights to several other emerging mobility systems that bear operational similarities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.