Modelling congested traffic on road networks: overcoming substantial limitations

交通拥堵是一个日益严重的问题，给道路使用者和非道路使用者带来了高昂的社会和经济成本。为了理解、规划和管理道路交通、拥堵和道路投资，交通网络模型具有很大的依赖性，因此，这些模型必须相当准确，或者至少没有严重缺陷。流量行为的一个重要部分是网络流量随时间的变化，例如，在一个当前的项目中，我们已经表明，现有的“分析”网络模型（具有时变交通流）与交通流的“流体流”模型（也称为LWR模型）的近似相当差。这导致无法正确地对拥堵（或“过度拥堵”）进行建模，并且无法忽略多个车道、车道变换、车道选择等，以及结果中的其他不一致。我们建议开发的方法来克服这些各种问题和现有的“分析”方法的局限性，以获得更健全的交通流理论的基础上的网络模型。这将建立在最新进展的基础上，将寻求保留“分析”方法的好处（例如，更易处理的数据要求，更可解释的结果），同时也保持与模拟方法的一致性，从而将使用中的两种主要方法联系起来。该领域的最新发展使这项工作成为可能，这项工作将在女王大学进行，主要涉及申请人（作为首席研究员）和一名研究助理。我们正在请求为后者提供资金，并为必要的旅行和计算机设备提供一些资金。

Traffic congestion is an ever-increasing problem with high social and economic costs to road users and nonusers. To understand, plan and manage road traffic, congestion and roads investment a heavy reliance is placed on traffic network models, hence it is important that these models be reasonably accurate or at least not seriously flawed. An essential part of traffic behaviour is variation in network flows over time, e.g., throughout the day, and in a current project we have shown that existing 'analytic' network models for this (with time-varying traffic flows) are rather poor approximations to a 'fluid flow' model (also called the LWR model) of traffic flow. This results in an inability to properly model congestion (or 'hypercongestion'), and to ignoring multiple lanes, lane changing, choice of lanes, etc., and to other inconsistencies in results. We propose to develop ways to overcome these various problems and limitations in existing 'analytic' approaches, to obtain network models that are more soundly based on traffic flow theory. This would build on recent advances, would seek to retain the benefits of an 'analytic' approach (e.g. more tractable data requirements, more interpretable results) while also retaining consistency with simulation approach, thus linking the two main approaches in use. The work is made possible by recent developments in the field, would be undertaken at Queen's university, and would mainly involve the applicant (as principal investigator) and one research assistant. We are requesting funding for the latter, plus some funding for necessary travel and computing equipment.