共同设计，使用户友好的工具来评估未来移动解决方案的影响
Co-Design to Enable User-Friendly Tools to Assess the Impact of Future Mobility Solutions
摘要：
未来移动解决方案的设计和它们所支持的移动系统的设计是紧密相连的。事实上，对新型移动解决方案的预期服务的了解将影响其设计和部署过程，而对其技术发展的见解可能会显著影响交通管理政策。这就需要工具来研究这种耦合，并根据不同的目标共同设计移动系统。我们提出了一个框架来解决这样的协同设计问题，利用协同设计的数学理论来构建和解决设计和部署多式联运系统的问题，从而自动驾驶汽车与微移动解决方案和公共交通共同服务出行需求，车队规模，车辆特性和公共交通服务频率。我们的框架是模块化和组合的，允许一个描述的设计作为简单组件的互连，并从系统的角度来解决它。此外，它需要一般的单调性假设，并自然地处理多个目标，为决策者提供合理的，可操作的解决方案。我们在华盛顿特区的案例研究中展示了我们的方法，USA.我们的工作表明有可能创建用户友好的优化工具，以系统地评估干预措施的成本和收益，并为未来的政策制定提供信息。
英文摘要：
The design of future mobility solutions and the design of the mobility systems they enable are closely coupled. Indeed, knowledge about the intended service of novel mobility solutions would impact their design and deployment process, whilst insights about their technological development could significantly affect transportation management policies. This requires tools to study such a coupling and co-design mobility systems in terms of different objectives. We present a framework to address such co-design problems, leveraging a mathematical theory of co-design to frame and solve the problem of designing and deploying an intermodal mobility system, whereby autonomous vehicles service travel demands jointly with micromobility solutions and public transit, in terms of fleets sizing, vehicle characteristics, and public transit service frequency. Our framework is modular and compositional, allowing one to describe the design as the interconnection of simple components and to tackle it from a systemic perspective. Moreover, it requires general monotonicity assumptions and naturally handles multiple objectives, delivering rational, actionable solutions for policy makers. We showcase our methodology in a case study of Washington D.C., USA. Our work suggests the possibility to create user-friendly optimization tools to systematically assess costs and benefits of interventions, and to inform policy-making in the future.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
