Spatiotemporal Closed-Loop-Optimal Dynamic Road Pricing for Urban Congestion Control

城市拥堵控制的时空闭环最优动态道路定价

• 批准号: RGPIN-2014-03959
• 负责人: Abdulhai, Baher
• 金额: $ 2.48万
• 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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=636291
• 关键词: Spatiotemporal; Closed; Loop; Optimal; Dynamic

Traffic congestion is reaching a crisis level in larger cities and metropolises in Canada and worldwide. The Greater Toronto and Hamilton Area (GTHA) in Ontario, Canada, is a vivid example in terms of widespread congestion on all modes, particularly roads. Congestion problems have key roots including: (1) lack of infrastructure spending to cope of population growth (lack of adequate supply), (2) unsustainable travel behavior and choices and heavy dependence of cars (excessive demand), (3) lack of efficiency in allocating demand to supply, possibly in real time (4) untamed urban sprawl, and (5) lack of integrated demand and supply management analytical tools. The proposed research focuses on dynamic congestion pricing as a pointed method/measure to manage demand generation and supply allocation and induce travel behavior changes towards urban sustainability. Numerous case studies and pilot deployments worldwide have investigated and demonstrated the potential of congestion pricing schemes in reducing the vehicular demand in congested urban areas, and the public’s response. However, stakeholders continue to struggle, particularly in Canada, with the dilemma of whether to toll or not to toll their roads; due to significant intertwine of technical, social and political challenges. These challenges are related to the difficulty of formulating and concurrently addressing the multifaceted nature of the congestion pricing problem into one analytical framework that can provide quantitative answers to proposed pricing schemes and policies. Such lack of precise and analytical answers renders policy makers ill equipped and the public fearful, ultimately leading to policy indecision and fierce public opposition to what can be a decisive and sustainable transportation solution, i.e. transportation and political gridlock. This research will develop a unified dynamic spatio-temporal (location and time specific) congestion pricing framework that tackles the key questions while considering three important and interrelated perspectives: economic, traffic engineering and travel behavior. The key questions include: (1) where and when to apply pricing, (2) what is the optimal spatio-temporal pricing structure, (2) what is impact on traffic congestion and road capacities (supply side), (3) what is the impact of social welfare, (4) what is the impact on travellers’ behavior and choice dimensions including mode choice, departure time choice and route choice (demand side). The proposed framework/system is based on: 1) control and optimization approaches for demand and supply management, 2) users discrete choices in response to pricing policies, and 3) real-time measurements to produce real-time dynamic tolls that can prevent potential traffic breakdowns. The proposed system is dynamic, stochastic, applicable to area wide or specific facilities, sensitive to distance, location and time of the day, maximizes network performance in terms of minimum travel cost, maximizes social welfare by avoiding monopoly pricing and addressing the external cost of congestion, and explicitly accounts for demand elasticity and users’ behavioral responses in terms of mode choice, departure time choice, and route choices. Further, with the increase of market penetration of pervasive sensors, it is anticipated in the near future that pollution can be directly measured from in-vehicle devices and communicated in real time via the Internet. The proposed platform will attempt to relate congestion pricing to the pollution level each individual vehicle contributes, to reduce adverse environmental impacts of congestion and enhance pricing equity.

加拿大安大略省的大多伦多和汉密尔顿地区（GTHA）的交通拥堵正在达到危机水平，所有交通方式都普遍拥堵，尤其是道路拥堵问题。关键根源包括：(1) 缺乏基础设施支出来应对人口增长（缺乏充足的供应），(2) 不可持续的出行行为和选择以及对汽车的严重依赖（需求过度），(3) 需求分配效率低下到供应，可能是实时的（4）不受控制的城市扩张，以及（5）缺乏综合的需求和供应管理分析工具拟议的研究重点是动态拥堵定价作为管理需求产生和供应分配并诱导的有针对性的方法/措施。世界各地的大量案例研究和试点部署已经调查并证明了拥堵收费在减少拥堵城市地区车辆需求方面的潜力，以及公众的反应，但利益相关者仍然在努力解决这一问题，特别是在加拿大。是否要面临的困境收费或不收费的道路；由于技术、社会和政治挑战的重大交织，这些挑战与将拥堵收费问题的多方面性制定并同时解决为一个分析框架的难度有关，该分析框架可以提供定量答案。缺乏精确和分析性的答案使得政策制定者缺乏准备，公众也感到恐惧，最终导致政策犹豫不决和公众对决定性和可持续的交通解决方案的强烈反对，即交通和政治僵局。研究意愿开发一个统一的动态时空（特定于位置和时间）拥堵定价框架，在解决关键问题的同时考虑三个重要且相互关联的观点：经济、交通工程和出行行为。关键问题包括：（1）何时何地适用。定价，(2)最优时空定价结构是什么，(2)对交通拥堵和道路通行能力（供给侧）有什么影响，(3)社会福利有什么影响，(4)有什么影响关于旅行者的行为和选择维度包括模式选择、出发时间选择和路线选择（需求方）。所提出的框架/系统基于：1）需求和供应管理的控制和优化方法，2）用户响应定价政策的离散选择，以及3）。实时测量产生实时动态收费，可以防止潜在的交通故障。所提出的系统是动态的、随机的，适用于区域范围或特定设施，对距离、位置和一天中的时间敏感，最大限度地提高网络性能。最小的出行成本，最大化的社会福利通过避免垄断定价和解决拥堵的外部成本，并明确考虑需求弹性和用户在模式选择、出发时间选择和路线选择方面的行为反应。此外，随着普及传感器市场渗透率的提高。预计在不久的将来，污染可以通过车载设备直接测量，并通过互联网实时传达。该平台将尝试将拥堵收费与每辆车造成的污染水平联系起来，以减少对环境的不利影响。拥堵并提高定价公平性。