Waiting Time Management, Its Consideration with Business Analytics, and Operating Autonomous Vehicles

等待时间管理、业务分析的考虑以及自动驾驶车辆的操作

• 批准号: RGPIN-2018-05638
• 负责人: Baron, Opher
• 金额: $ 3.79万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711719
• 关键词: Waiting; Time; Management; Its; Consideration

My research team has made substantial progress over the last 5 years. This proposal examines (I) queueing theory and waiting time management, (II) waiting time management with analytics in healthcare, and (III) the impact of Autonomous Vehicles (AVs) on welfare. I. Queueing Theory and Waiting Time Management We developed the Queueing and Markov Chain Decomposition (QMCD) methodology that international queueing theorists currently use. To further disseminate QMCD, we will characterize the problems it can solve, such as multi-servers queues. We will study such queues in the presence of priority and abandonments. These, well-known, open, problems are also appropriate for traffic intersections and will support project III. We will continue to study queueing location models that are critical for firms' expansions. The failure of Target in Canada demonstrates the consequence of poor expansion planning. We will study healthcare related phenomena in queues in the presence of triage and service level targets (see, e.g., Canadian Triage and Acuity Scale) to support project II. II. Waiting Time Management with Analytics in Healthcare A critical healthcare issue is the management of waiting in Emergency Departments (EDs) and for elective surgeries. For example, the wait for 10% of adult surgeries in BC is more than 31 weeks, see https://swt.hlth.gov.bc.ca/faces/Wooden.xhtml. We will use data to establish effective management of EDs, calculate the imputed healthcare effects of wait time reduction in EDs, help EDs to improve their processes, and devise effective algorithms to schedule surgeries while considering downstream medical and surgical beds. III. The Impact of Autonomous Vehicles (AVs) on Quality of Life AVs may soon compose the backbone of land transportation, yet little research on AVs' impact on welfare is available to support policies on their deployment. We will study how AVs can be effectively share, consider sizes of AVs and lane allocation, analyze the safety and healthcare implications of AVs (annually, nearly 1.3 million people are killed in accidents, see http://asirt.org/initiatives/informing-road-users/road-safety-facts/road-crash-statistics), consider taxation of electric AVs in the replacement of gas tax to support infrastructure, and examine how to coordinate AVs. Contributions: The proposed research program will: train highly qualified personnel, improve the control of important applications, and develop new theories. Specifically, (I) will lead to a breakthrough in queueing theory via the assimilation of the QMCD methodology we developed, (II) will improve the healthcare delivery process and its results for emergency and pre-surgery patients, and (III) will provide, science based, guidelines for Canadian policy makers on the deployment of AVs.

我的研究团队在过去五年中取得了重大进展。该提案研究了（I）排队理论和等待时间管理，（II）医疗保健中的等待时间管理和分析，以及（III）自动驾驶汽车（AV）对福利的影响。 I.排队论与等候时间管理 我们开发了目前国际上流行理论家使用的马尔可夫链分解（QMCD）方法。为了进一步推广QMCD，我们将描述它可以解决的问题，如多服务器队列。我们将研究存在优先级和放弃的排队。这些众所周知的开放性问题也适用于交通交叉口，并将支持项目III。我们将继续研究对企业扩张至关重要的企业选址模式。塔吉特在加拿大的失败表明了扩张计划不力的后果。我们将研究在存在分流和服务水平目标的情况下队列中的医疗保健相关现象（参见，例如，加拿大分类和敏锐度量表），以支持项目二。 二.医疗保健中的等待时间管理与分析 一个关键的医疗保健问题是在急诊室（ED）和择期手术等待的管理。例如，卑诗省10%的成人手术等待时间超过31周，见https://swt.hlth.gov.bc.ca/faces/Wooden.xhtml。我们将使用数据来建立对急诊室的有效管理，计算急诊室等待时间减少的估算医疗效果，帮助急诊室改善流程，并设计有效的算法来安排手术，同时考虑下游医疗和外科病床。 三.自动驾驶汽车（AV）对生活质量的影响 自动驾驶汽车可能很快就会成为陆地交通的支柱，但关于自动驾驶汽车对福利的影响的研究很少，无法支持其部署政策。我们将研究如何有效地共享自动驾驶汽车，考虑自动驾驶汽车的大小和车道分配，分析自动驾驶汽车的安全和医疗影响（每年有近130万人死于事故，请参阅http：//asirt.org/initiatives/informing-road-users/road-safety-facts/road-crash-statistics），考虑电动自动驾驶汽车的税收以取代汽油税来支持基础设施，并研究如何协调自动驾驶汽车。 贡献：拟议的研究计划将：培养高素质的人才，提高重要应用的控制，并开发新的理论。具体而言，（I）将通过我们开发的QMCD方法的同化，导致医疗理论的突破，（II）将改善急诊和术前患者的医疗保健提供过程及其结果，以及（III）将为加拿大政策制定者提供基于科学的AV部署指南。