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.

该项目将创建新颖的方法，以最大程度地提高卡车参与排队，这是指动车以较小的拖车间分离行驶，以减少空气动力学的阻力。近年来，货运部门一直在大量投资排型技术，这主要是由于降低卡车能源的巨大好处。该项目将调查促进广泛的卡车排的基本问题，同时考虑到美国卡车运输部门的高度分裂，同时考虑1）单独的卡车偏好； 2）包括不同起源，目的地和计划的出发时间的卡车在形成排； 3）保存卡车信息隐私。该研究的结果将与该行业合作生产，将有助于为美国的卡车排量实施提供信息，从而获得最大的收益。这项研究还与日益增长的社会强调个人福祉，包容性，隐私和网络安全相吻合。通过系统的教育和外展工作，各种学生团体将暴露于卡车排和技术授权的智能机动性的主题。该项目的目的是建立一个理论基础，以考虑到卡车的偏好，包容和隐私保护，以最大化卡车的参与度。首先设计了卡车和排平台之间的互动过程，以促进为每辆卡车的排量伙伴的偏好清单。然后，该研究调查了两种用于排量参与最大化的方法：一个以稳定的卡车为中心，将卡车划分为循环偏好的各方；通过探索有效解决方案方法的极端点的半融合性，其他诉诸于整数编程。进一步开发了多个纳入措施，并将其整合到排成的参与最大化中。为了在寻求排成机会的同时保留隐私，对构建卡车偏好列表进行了构思和检查。设计的核心是一个两云的体系结构，具有秘密钥匙拆分，密文的重新加密和混淆，可利用所选加密系统的添加性同构属性。基于实际货运数据的分类卡车流将被构造，并用于测试和评估不同地理量表的不同研究组件。该项目的结果不仅将有助于丰富卡车排的文献，而且对具有运营相似之处的其他几种新兴移动系统提供了见解。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准通过评估来获得支持的。