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

通过偏好、包容性和隐私保护最大限度地提高卡车编队参与度

• 批准号: 2221418
• 负责人: Bo Zou
• 金额: $ 29.04万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2221418&HistoricalAwards=false
• 关键词: Maximizing; Truck; Platooning; Participation; Preferences

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.

该项目将创造新的方法，以最大限度地提高卡车在排队中的参与，这是指卡车在小卡车间的间隔，以减少空气动力学阻力组行驶。近年来，卡车运输行业一直在大力投资车队技术，主要是由于减少卡车能源使用的巨大好处。该项目将调查促进广泛的卡车排队的基本问题，同时考虑1）个人卡车偏好，鉴于美国卡车运输部门的高度分散; 2）包括不同起源，目的地和计划出发时间的卡车组成队列;以及3）保护卡车信息隐私。研究结果将与行业合作产生，将有助于为美国的卡车排队实施提供信息，以获得最大的利益。该研究还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保持一致。不同的学生团体将通过系统的教育和推广工作，接触到卡车排队和技术驱动的智能移动性的主题。该项目的目标是建立一个理论基础，最大限度地提高卡车排队参与考虑到卡车的喜好，包容性和隐私保护。首先设计了一个卡车和排队平台之间的交互过程，以便于为每个卡车构建排队伙伴的偏好列表。然后，研究了两种方法的排队参与最大化：一个中心的稳定划分卡车到各方的循环偏好;其他诉诸整数规划与探索的极值点的半完整性的有效的解决方案。多重包容性措施进一步发展和整合到排队参与最大化。为了保护隐私，同时寻求排队的机会，加密计算设计的构思和检查构建卡车偏好列表。该设计的核心是一个双云架构，具有密钥分裂，密文重新加密和混淆，它利用了所选密码系统的加性同态属性。基于真实世界货运数据的分类卡车流量将被构建并用于测试和评估不同地理尺度的不同研究组成部分。该项目的成果不仅将有助于丰富卡车排队文献，还将为其他几种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知识价值和更广泛的影响审查标准进行评估，被认为值得支持。