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新冠疫情对出行和旅行需求产生影响。

COVID-19 impacts on mobility and travel demand.

作者信息

Shemer Lisa, Shayanfar Elham, Avner Jonathan, Miquel Roberto, Mishra Sabyasachee, Radovic Mark

机构信息

Maryland State Highway Administration, Travel Forecasting and Analysis Division, Office of Planning and Preliminary Engineering, Baltimore, MD 21202, United States.

Itenology Inc., Columbia, MD 21045, United States.

出版信息

Case Stud Transp Policy. 2022 Dec;10(4):2519-2529. doi: 10.1016/j.cstp.2022.11.011. Epub 2022 Nov 14.

Abstract

Since the beginning of the COVID-19 pandemic, many travel restriction policies were implemented to reduce further spread of the virus. These measures significantly affected travel demand to levels which could not have been anticipated by most planners in transportation agencies. As the pandemic has proven to have significant short-term impacts, it is anticipated that some of these impacts may translate to longer-term impacts on overall travel behavior and the movement of people and goods. Beyond the pandemic, the observed travel patterns during this period also provides a great opportunity for planners to assess policies such as work from home and remote learning as strategies to manage travel demand. This study provides a scenario analysis framework to re-evaluate travel demand forecasts under uncertain future conditions using the Maryland Statewide Transportation Model (MSTM). Model parameters associated with working from home, household income, changes in discretionary travel, distance learning, increased e-commerce, vehicle occupancy and mode choice were identified. Parameter values were assigned under the various scenarios using employer surveys on workforce teleworking and observed data on e-commerce growth and shopping behavior. The main findings of this study capture the sensitivities of systemwide vehicle miles travel, and vehicle hours travel under different scenarios and implications on future investment decisions. The study found that future investments under the scenarios remain beneficial to systemwide performance and therefore justified. Although this study focuses on the state of Maryland, the scenario framework and parameter definitions can be used in other states or agencies within a travel demand model environment.

摘要

自新冠疫情开始以来,实施了许多旅行限制政策以减少病毒的进一步传播。这些措施极大地影响了旅行需求,降至大多数交通机构规划者无法预见的水平。由于事实证明疫情具有重大短期影响,预计其中一些影响可能会转化为对整体出行行为以及人员和货物流动的长期影响。除了疫情之外,这一时期观察到的出行模式也为规划者提供了一个绝佳机会,用以评估诸如居家办公和远程学习等政策作为管理出行需求的策略。本研究提供了一个情景分析框架,以使用马里兰州全州交通模型(MSTM)在不确定的未来条件下重新评估出行需求预测。确定了与居家办公、家庭收入、自由裁量出行变化、远程学习、电子商务增长、车辆乘员率和出行方式选择相关的模型参数。使用雇主关于劳动力远程办公的调查以及电子商务增长和购物行为的观测数据,在各种情景下分配参数值。本研究的主要发现揭示了不同情景下全系统车辆行驶里程和车辆行驶时间的敏感性以及对未来投资决策的影响。研究发现,情景下的未来投资对全系统性能仍然有益,因此是合理的。尽管本研究聚焦于马里兰州,但情景框架和参数定义可在出行需求模型环境中的其他州或机构使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfd/9661421/6724354c6013/gr1_lrg.jpg

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