Intelligent Transportation Planning

智能交通规划

• 批准号: RGPIN-2022-03916
• 负责人: Errico, Fausto
• 金额: $ 2.62万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753904
• 关键词: Intelligent; Transportation; Planning

The road-transportation sector represents nowadays a major contributing factor to the count of Green-House Gas emissions. This contribution is mostly due to the large ratio of vehicles powered by traditional fossil fuels, and by the constant rise of the number of vehicles on the roads. The transportation sector has, however, the perspective of undergoing an authentic technological revolution, labelled as Transportation 4.0 (Tr4), whose main elements are: 1) the transition towards the electrification of the transportation system, 2) the adoption of self-driving and Autonomous Vehicles (AVs), 3) the advances in Information Technology, 4) the widespread collection and storage of transportation data, and 5) the instantaneous and distributed access to computing resources. While the technological advances implicit in the Tr4 set up the conditions for more sustainable and efficient transportation systems, their management becomes dramatically more challenging. When surveying the scientific literature, one finds that there is a considerable lack of methodologies to address the challenges presented by the Tr4, both in the context of transit systems, as well as in freight distribution. Therefore, the main objective of this proposal is to develop decision-support tools to enable the transportation industry to fully profit from the opportunities given by the Tr4. The proposed methods are rooted in the fields of operations research and artificial intelligence. This research program is organized around two themes. The first theme considers transit systems and focuses on planning problems arising in the integration of on-demand services with traditional transit. This is done by adopting a modeling framework named Semi-flexible Transit System (STS). STSs aim to provide demand-responsive service within the framework of regularly scheduled transit. Combining characteristics of traditional and on-demand systems, STSs require an extremely complex planning activity. More specifically, this proposal aims to develop the methodology to incorporate a fleet of AVs in the operations planning of STSs, and build a simulation framework to analyze the performance of a system integrating STSs with traditional transit, and its impact on the mobility at a city-scale. The second theme considers freight transportation and focuses on stochastic and dynamic routing problems arising in the context of the Tr4. More specifically, this second theme aims to develop decision-support tools for real-time routing of vehicles under stochastic and dynamic traffic conditions, as well as dynamic policies for routing and charging operations when operating a fleet of battery-equipped electric vehicles. By developing tools to enable the Tr4 revolution, the anticipated impact of this research program is to provide more sustainable and more equitable transportation services, both in terms of public transit, as well as freight distribution.

道路运输部门目前是温室气体排放量的主要贡献因素。这一贡献主要是由于传统化石燃料驱动的车辆比例很大，以及道路上车辆数量的不断增加。然而，运输部门有可能经历一场真正的技术革命，称为运输4.0（Tr4），其主要内容是：1）交通系统向电气化过渡，2）自动驾驶和自动驾驶汽车（AV）的采用，3）信息技术的进步，4）交通数据的广泛收集和存储，以及5）对计算资源的即时和分布式访问。虽然Tr4中隐含的技术进步为更可持续和更高效的运输系统创造了条件，但其管理变得更具挑战性。在调查科学文献时，人们发现，无论是在过境系统还是在货物分配方面，都相当缺乏应对第四次贸易试验所带来挑战的方法。因此，本提案的主要目标是开发决策支持工具，使运输业能够充分利用Tr4带来的机会。所提出的方法植根于运筹学和人工智能领域。本研究计划围绕两个主题展开。第一个主题考虑过境系统，重点是将按需服务与传统过境结合起来所产生的规划问题。这是通过采用一个名为半柔性交通系统（STS）的建模框架。运输服务站的目标是在定期安排的过境框架内提供需求响应服务。结合传统和按需系统的特点，STS需要一个非常复杂的规划活动。更具体地说，该提案旨在开发将无人驾驶汽车车队纳入STS运营规划的方法，并建立一个仿真框架来分析STS与传统交通相结合的系统的性能，以及其对城市规模的流动性的影响。第二个主题考虑货运，并侧重于随机和动态的路由问题中出现的Tr4的背景下。更具体地说，第二个主题旨在开发随机和动态交通条件下车辆实时路由的决策支持工具，以及在运营配备电池的电动汽车车队时路由和充电操作的动态策略。通过开发工具来实现Tr4革命，该研究计划的预期影响是在公共交通和货运配送方面提供更可持续和更公平的运输服务。