21st Century Traffic Control and Management for Large Congested Cities: Exploiting Pervasive Vehicular Automation, Connectivity and Sharing

21 世纪拥堵大城市的交通控制和管理:利用普遍的车辆自动化、连通性和共享

基本信息

  • 批准号:
    RGPIN-2019-05102
  • 负责人:
  • 金额:
    $ 2.62万
  • 依托单位:
  • 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

项目摘要

The objective of this research program is to develop integrated traffic control systems for smart cities in the 21st century that exploit emerging innovations in vehicular automation and connectivity and shared mobility services. Cities in Canada and worldwide are growing increasingly busy, a trend that perpetually rises. Populations and human activity are growing, while transportation infrastructure is limited by space, financial and environmental constraints. With trending vehicular automation and connectivity (e.g. the google car) and vehicle and ride sharing (e.g. uberPOOL) our transportation systems and our cities are at the precipice of a paradigm shift, second only to the first revolution of introducing the car itself in the early 1900s. Technology and new transportation services are rapidly transforming the fundamentals of how our cities shapeup and how we move within them. However, we are not yet fully prepared for the consequences. The boldest vision for smart transportation in smart cities of the future is automated, connected, green and shared. The net effect, however, is far from certain, and can be significantly positive or drastically negative, depending on how we explicitly design and exploit such innovations and manage their evolution and adoption in society. We have yet to build science and tools to concurrently manage both the demand (trips on the road) and supply (infrastructure capacities and efficiency) in the context of large cities. This research, therefore, focuses on the context of large and complex transportation systems in cities, and not on vehicular technology creation per se. We focus on how to exploit disruptive transportation technologies and services to maximize the societal benefits while avoiding potential risks and unintended consequences. More specifically, we will use modern machine learning coupled with fundamental traffic flow theory and economics to: (1) quantify the impacts of transformative technologies on the transportation system and its performance and (2) create traffic control, optimization and management methods, tools, strategies, and policies that guide the inevitable transformation in a positive direction, improving the economic, social, and environmental sustainability of our future cities. We will develop systems for trip pricing to avoid exacerbating sprawl and traffic congestion. We will also exploit high levels of automation and pervasive connectivity to build new traffic control systems that boost infrastructure capacity. The new systems and policies will be implementable and enforceable using technology, with minimal public infrastructure and at reasonable costs. The significance of this research is to prepare Canada for the era of smart cities at the core of which is smart transportation. This is essential for the economic, social, and environmental sustainability and wellbeing of Canada.
该研究计划的目标是为21世纪的智慧城市开发综合交通控制系统,利用车辆自动化和连接以及共享移动服务方面的新兴创新。加拿大和世界各地的城市正变得越来越繁忙,这一趋势还在持续上升。人口和人类活动不断增长,而交通基础设施受到空间、资金和环境约束的限制。随着汽车自动化和互联(如谷歌汽车)以及汽车和拼车(如uberPOOL)的发展趋势,我们的交通系统和城市正处于范式转变的边缘,仅次于20世纪初引入汽车本身的第一次革命。技术和新的交通服务正在迅速改变我们城市的基本形态和我们在城市中出行的方式。然而,我们还没有为后果做好充分准备。未来智慧城市中智能交通最大胆的愿景是自动化、互联、绿色和共享。然而,净效应还远未确定,可能是显著的积极影响,也可能是极大的消极影响,这取决于我们如何明确地设计和利用这些创新,以及如何管理它们在社会中的演变和采用。在大城市的背景下,我们还需要建立科学和工具来同时管理需求(道路上的行程)和供应(基础设施的能力和效率)。因此,本研究侧重于城市中大型和复杂的运输系统的背景,而不是车辆技术创造本身。我们专注于如何利用颠覆性的运输技术和服务,以最大限度地提高社会效益,同时避免潜在的风险和意想不到的后果。更具体地说,我们将使用现代机器学习与基础交通流理论和经济学相结合:(1)量化变革技术对交通系统及其性能的影响;(2)创建交通控制、优化和管理方法、工具、战略和政策,引导不可避免的转型朝着积极的方向发展,提高我们未来城市的经济、社会和环境可持续性。建立出行定价机制,避免城市蔓延和交通拥堵加剧。我们还将利用高水平的自动化和无处不在的连接,建立新的交通控制系统,提高基础设施的能力。新的制度和政策将是可实施和可执行的,利用技术,以最少的公共基础设施和合理的成本。这项研究的意义在于让加拿大为智慧城市时代做好准备,而智慧城市的核心是智能交通。这对加拿大的经济、社会和环境的可持续性和福祉至关重要。

项目成果

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Abdulhai, Baher其他文献

A bi-level distributed approach for optimizing time-dependent congestion pricing in large networks: A simulation-based case study in the Greater Toronto Area
Large-Scale Evacuation Using Subway and Bus Transit: Approach and Application in City of Toronto
  • DOI:
    10.1061/(asce)te.1943-5436.0000371
  • 发表时间:
    2012-10-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Abdelgawad, Hossam;Abdulhai, Baher
  • 通讯作者:
    Abdulhai, Baher
Real-Time Transportation Mode Detection via Tracking Global Positioning System Mobile Devices
A comparative assessment of multi-sensor data fusion techniques for freeway traffic speed estimation using microsimulation modeling
Multiagent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC): Methodology and Large-Scale Application on Downtown Toronto

Abdulhai, Baher的其他文献

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{{ truncateString('Abdulhai, Baher', 18)}}的其他基金

21st Century Traffic Control and Management for Large Congested Cities: Exploiting Pervasive Vehicular Automation, Connectivity and Sharing
21 世纪拥堵大城市的交通控制和管理:利用普遍的车辆自动化、连通性和共享
  • 批准号:
    RGPIN-2019-05102
  • 财政年份:
    2021
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
21st Century Traffic Control and Management for Large Congested Cities: Exploiting Pervasive Vehicular Automation, Connectivity and Sharing
21 世纪拥堵大城市的交通控制和管理:利用普遍的车辆自动化、连通性和共享
  • 批准号:
    RGPIN-2019-05102
  • 财政年份:
    2020
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
21st Century Traffic Control and Management for Large Congested Cities: Exploiting Pervasive Vehicular Automation, Connectivity and Sharing
21 世纪拥堵大城市的交通控制和管理:利用普遍的车辆自动化、连通性和共享
  • 批准号:
    RGPIN-2019-05102
  • 财政年份:
    2019
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
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
  • 财政年份:
    2018
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
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
  • 财政年份:
    2017
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
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
  • 财政年份:
    2016
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
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
  • 财政年份:
    2015
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
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
  • 财政年份:
    2014
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
High performance optimization of integrated transportation management methods for emergency evacuation
应急疏散综合运输管理方法的高性能优化
  • 批准号:
    205022-2009
  • 财政年份:
    2013
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual
High performance optimization of integrated transportation management methods for emergency evacuation
应急疏散综合运输管理方法的高性能优化
  • 批准号:
    205022-2009
  • 财政年份:
    2012
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Discovery Grants Program - Individual

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