Multimodal Systems Design with Network Interactions

人们越来越关注多式联运，以支持城市交通。自2000-2001年以来，加拿大政府在与联邦公共交通相关的基础设施上投资了50多亿加元，并将公共交通确定为建设加拿大基金下的五个国家优先事项之一。然而，许多公共交通机构继续使用最传统的系统和替代方案进行规划和运营，尽管移动的技术和替代多式联运商业模式（例如Zipcar、SF Park等初创公司）在增长。这是因为计算机模型无法回答，例如，“如果市中心的停车设施费或Zipcar费率补贴10%，汽车、公交和自行车的流量将如何变化？" 为了更好地理解多模式系统，需要考虑新的设计。多个交通运营商（例如Metrolinx和多伦多交通委员会等公共机构，或多伦多的BIXI自行车共享等私营公司）将随着城市地区的密度增加而更多地互动。运输系统（公共和私营，大型和小型）并非存在于真空中，但这些系统的许多运营商在规划新设计时继续这样假设。可能会出现冲突和错失合作机会。少数考虑运营商之间竞争的人只关注传统的固定路线公交服务（例如公共汽车和火车服务），而不是更广泛的现代多式联运系统，包括停车，汽车共享或需求响应式公交。 这项研究解决了这些问题，使现代多式联运解决方案的设计大区域的发展。首先，将开发新的模型，以统一的、基于活动的方式分析家庭对大多数多式联运替代方案的出行需求。其次，这些模型将被用来研究不同的多式联运的相互作用，在设计策略之间的运输系统运营商使用博弈论和多目标优化。其结果可能会减少机构之间的潜在冲突，并鼓励合作或互惠战略，以改善社会福利和城市的可持续性。

There is an increasing interest in multimodal transportation to support urban mobility. The Government of Canada invested over $5 billion in federal public transit-related infrastructure since 2000-2001, and has identified public transit as one of five national priorities under the Building Canada Fund. Yet, many public transport agencies continue to plan and operate using the most conventional systems and alternatives, despite the growth in mobile technologies and alternative multimodal transport business models (e.g. startups like Zipcar, SF Park). This is because computer models cannot answer, for example, "How would the flow of cars, transit, and bikes shift if parking facility fees or Zipcar rates in downtown were subsidized by 10%?" To better understand multimodal systems, new designs need consideration. Multiple transport operators (e.g. public agencies like Metrolinx and Toronto Transit Commission, or private companies like BIXI bike sharing in Toronto) will interact more as urban regions become denser. Transport systems (both public and private, large and small) do not exist in a vacuum, but many operators of these systems continue to assume so when planning new designs. Conflicts and missed cooperative opportunities may arise. The few that consider competition between operators focus only on conventional fixed route transit service (e.g. bus and train service), but not on the wider range of modern multimodal systems that can include parking, car sharing, or demand responsive transit. This research addresses these problems to enable the design of modern multimodal solutions for mega-region development. First, new models will be developed to analyze household travel demand for most multimodal alternatives in a unified, activity-based manner. Second, these models will be used to study different multimodal interactions in design strategies between transport system operators using game theory and multiobjective optimization. The outcome may reduce potential conflicts between agencies and encourage cooperative or mutualistic strategies to improve social welfare and urban sustainability.