ANALYTICAL MODELING AND OPTIMIZATION OF URBAN PUBLIC TRANSIT SYSTEMS

城市公共交通系统的分析建模和优化

• 批准号: RGPIN-2022-03040
• 负责人: Wirasinghe, Sumedha
• 金额: $ 3.13万
• 依托单位: University of Calgary
• 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=749444
• 关键词: ANALYTICAL; MODELING; OPTIMIZATION; URBAN; PUBLIC

ANALYTICAL MODELING OF URBAN PUBLIC TRANSIT SYSTEMS Urban public transit plays an essential role in developing a sustainable transport system that provides increased mobility with an economy of scale. The long-term goal of the research program is to gain results & insights to improve the design, planning & operation of public transit.  Over 5 years, the research program will formulate a novel transit service evaluation metric and incorporate new advancement in technology (e.g. transit automation) while taking into consideration the needed adaptation in transit service and route network (e.g. demand responsive transit). These short-term objectives to be achieved are as follows with the first three objectives & previous research enabling the final two: 1: Develop a Route Level of Service (LofS) measure: Currently used LofS measures are arbitrary. Our objective is to find the LofS of an optimized route for each aspect & a unified LofS to compare routes and identify improvements. . 2. Analyze a fully Autonomous Bus Route: Autonomous systems are expected to evolve rapidly. Our objective is to study a fully autonomous bus that will serve a long route on regular roads, for travel from many origins to many destinations.   3. Analyze Electric Bus (EB) Reliability: Buses need time-points where they are held if running early. Additionally, EB's require identified stops at which batteries must be recharged causing unreliability. Our objective is to determine the time points chosen to be battery charging points to reduce unreliability. 4. Model a Demand Responsive Transit (DRT) Local Network: DRT is key to providing sustainable service in low demand situations. Our objective is to investigate the conditions under which communities become suitable for DRT. 5. Model Major Transit Networks: Transit agencies revise networks every few years. Our objectives are to optimize irregular transit networks, & propose how & when to transition from an existing network to a significantly different network.  The focus of the Short Term Objectives: Objective functions will be developed to include passenger time costs plus operating, environmental & capital costs. An analytical approach is taken to develop normative models & undertake optimization & reliability analysis. We will first focus on three individual route aspects that are currently neglected & using those results, & other available research, study a local transit network and one major transit network. The methodology can be applied to any route/network & provide significant insight. A unique aspect is to investigate the use of an "optimal" amount of data based on normative modeling as opposed to "big" data. The novelty here is the use of normative, continuum, analytical models and mostly calculus-based optimization to obtain deeply penetrative understanding of the issues. The significance is the contribution to the mobility of Canadians given the increasingly important role of transit in a sustainable society.

城市公共交通系统的分析模型城市公共交通在发展可持续的交通系统方面发挥着至关重要的作用，这种交通系统提供了更大的机动性和规模经济。该研究计划的长期目标是获得成果和见解，以改进公共交通的设计、规划和运营。该研究计划将在5年内制定一个新的公共交通服务评估指标，并纳入新的技术进步(例如，公共交通自动化)，同时考虑到公共交通服务和路线网络(例如，需求响应型公共交通)所需的适应。这些要实现的短期目标如下：前三个目标&之前的研究使最后两个成为可能：1：制定路径服务水平(LOFS)衡量标准：目前使用的LOFS衡量标准是任意的。我们的目标是找到每个方面的最优路径的LOF&一个统一的LOF来比较路径并确定改进。。2.分析完全自主的公交路线：预计自动公交系统将迅速发展。我们的目标是研究一种完全自动驾驶的巴士，它将服务于常规道路上的一条长途路线，从多个起点到许多目的地。分析电动公交车(EB)的可靠性：如果公交车运行得早，需要确定停放的时间点。此外，EB要求标识电池必须充电的停靠点，这会导致不可靠。我们的目标是确定选定的时间点作为电池充电点，以减少不可靠性。4.建立需求响应运输(DRT)本地网络模型：需求响应运输是在低需求情况下提供可持续服务的关键。我们的目标是调查社区变得适合DRT的条件。5.主要交通网络模型：交通机构每隔几年修订一次网络。我们的目标是优化不规范的交通网络，并提出如何以及何时从现有网络过渡到显著不同的网络。短期目标的重点：将开发目标函数，以包括乘客时间成本加上运营、环境和资本成本。采用解析的方法建立规范的模型，进行优化和可靠性分析。我们首先将重点放在目前被忽视的三个单独的路线方面&利用这些结果和其他现有的研究，研究一个本地交通网络和一个主要的交通网络。该方法可以应用于任何路由/网络&提供重要的洞察力。一个独特的方面是研究基于规范建模的“最佳”数据量的使用，而不是“大数据”。这里的新奇之处在于使用规范的、连续的、分析的模型和主要基于微积分的优化来获得对问题的深入深入的理解。其重要意义在于，鉴于过境在可持续社会中发挥着越来越重要的作用，它对加拿大人的流动性作出了贡献。