Since its outbreak in December 2019, COVID-19 has spread rapidly across the world. To slow down the spread of the pandemic, various countries have implemented a series of policies and measures. The transportation system is not only an important carrier for COVID-19, but also a vital means for the prevention and control of the spread of the pandemic. Therefore, most anti-pandemic measures are based on travel restrictions, thereby slowing down the spread of the pandemic. As a result, because of the impact of the pandemic and corresponding control measures, the transportation system has undergone tremendous changes. By analyzing the evolution of the transportation system in response to the influence of COVID-19, it is possible to better understand socioeconomic changes and the changes in residents' daily life. Based on rich license plate recognition data, the characteristics of urban motorized travel under the influence of COVID-19 has been analyzed. According to the processes associated with the control of the pandemic and the resumption of work and production, the analysis period is divided into four stages. The changes in indicators of macroscopic traffic status are analyzed for each stage. The three types of typical motor vehicle groups (i.e., non-localized operating vehicles, taxis, and localized operating vehicles) are characterized by the traffic flow they contribute, the number of vehicles in transit, the average travel intensity, the average daily travel time of a vehicle, the average daily travel distance of a vehicle, and the spatiotemporal distributions of origins and destinations of trips. These data clarify the spatiotemporal evolution characteristics of peoples’ travel behavior at different stages of the pandemic. The results of data analysis show that COVID-19 has deeply changed the motorized travel behavior of urban residents. In the initial stage of resumption of work and production, the willingness to engage in motorized travel had decreased significantly compared with that in the first stage. This willingness gradually resumed until the third and fourth stages, but still did not fully reach the level before the onset of the pandemic. Specifically, the traffic status during morning and evening peaks has basically recovered, and has even increased beyond the level before the pandemic; however, a certain gap was still found between off-peak hours. There were also significant differences in the extent to which different types of vehicles were affected by the pandemic. Among these, taxis were impacted the most by the pandemic. In the fourth stage (at the end of April), the average daily travel time of a vehicle and the average daily travel distance of a vehicle still decreased by 29.25% and 22.63% compared with the first stage, respectively. The operating time of many taxis was shortened from 22:00 PM to 19:00 PM. The spatiotemporal characteristics of vehicles show that the reduction of flexible travel demand (e.g., shopping, catering, and entertainment) is key to the reduction of the travel demand of the road network. This research provides data support for the implementation of traffic control measures under future grave public health events and enables the formulation of urban traffic policies in the post COVID-19 era.

自 2019 年 12 月爆发以来，COVID-19 已在全球迅速传播。为减缓疫情蔓延，各国实施了一系列政策措施。交通运输系统不仅是COVID-19的重要载体，也是防控疫情蔓延的重要手段。因此，大多数抗疫措施都是以旅行限制为基础，从而减缓疫情的传播。因此，由于疫情的影响和相应的管控措施，交通系统发生了巨大的变化。通过分析交通系统因应COVID-19的影响而发生的演变，可以更好地了解社会经济变化和居民日常生活的变化。基于丰富的车牌识别数据，分析了COVID-19影响下的城市机动出行特征。根据疫情控制和复工复产的进程，分析期分为四个阶段。分析各阶段宏观交通状况指标的变化情况。三类典型机动车群体（即外地营运车辆、出租车、本地营运车辆）通过其贡献的交通流量、过境车辆数量、平均出行强度、平均日出行时间来表征车辆的行驶里程、车辆日均行驶里程、出行始发地和目的地的时空分布。这些数据阐明了疫情不同阶段人们出行行为的时空演变特征。数据分析结果表明，COVID-19深刻改变了城市居民的机动出行行为。复工复产初期，机动出行意愿较第一阶段明显下降。这种意愿直到第三、第四阶段才逐渐恢复，但仍未完全达到疫情爆发前的水平。具体来说，早晚高峰的交通状况已基本恢复，甚至超过了疫情前的水平；但与非高峰时段仍存在一定差距。不同类型的车辆受疫情影响的程度也存在显着差异。其中，出租车受疫情影响最为严重。第四阶段（4月底），车辆日均出行时间和车辆日均出行距离仍较第一阶段分别下降29.25%和22.63%。不少出租车的运营时间从中午22:00缩短至晚上19:00。车辆时空特征表明，灵活出行需求（如购物、餐饮、娱乐）是减少路网出行需求的关键。该研究为未来重大公共卫生事件下交通管制措施的实施提供数据支撑，并为后COVID-19时代城市交通政策的制定提供依据。