State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Min-Hang District, Shanghai 200240, China.
Smart City and Intelligent Transportation Interdisciplinary Center, College of Future Transportation, Chang'an University, Wei-Yang District, Xi'an 710021, China.
Int J Environ Res Public Health. 2022 Jun 23;19(13):7665. doi: 10.3390/ijerph19137665.
The tremendous impact of the novel coronavirus (COVID-19) on societal, political, and economic rhythms has given rise to a significant overall shift from pre- to post-pandemic policies. Restrictions, stay-at-home regulations, and lockdowns have directly influenced day-to-day urban transportation flow. The rise of door-to-door services and the demand for visiting medical facilities, grocery stores, and restaurants has had a significant impact on urban transportation modal demand, further impacting zonal parking demand distribution. This study reviews the overall impacts of the pandemic on urban transportation with respect to a variety of policy changes in different cities. The parking demand shift was investigated by exploring the during- and post-COVID-19 parking policies of distinct metropolises. The detailed data related to Melbourne city parking, generated by the Internet of things (IoT), such as sensors and devices, are examined. Empirical data from 2019 (16 March to 26 May) and 2020 (16 March to 26 May) are explored in-depth using explanatory data analysis to demonstrate the demand and average parking duration shifts from district to district. The results show that the experimental zones of Docklands, Queensbery, Southbanks, Titles, and Princess Theatre areas have experienced a decrease in percentage change of vehicle presence of 29.2%, 36.3%, 37.7%, 23.7% and 40.9%, respectively. Furthermore, on-street level analysis of Princess Theatre zone, Lonsdale Street, Exhibition Street, Spring Street, and Little Bourke Street parking bays indicated a decrease in percentage change of vehicle presence of 38.7%, 56.4%, 12.6%, and 35.1%, respectively. In conclusion, future potential policymaking frameworks are discussed that could provide further guidance in stipulating epidemic prevention and control policies, particularly in relation to parking regulations during the pandemic.
新型冠状病毒（COVID-19）对社会、政治和经济节奏的巨大影响导致了从大流行前政策到大流行后政策的重大整体转变。限制、居家规定和封锁直接影响了日常城市交通流量。上门服务和对访问医疗设施、杂货店和餐馆的需求的增加对城市交通模式需求产生了重大影响，进一步影响了区域停车需求分布。本研究综述了大流行对城市交通的总体影响，以及不同城市的各种政策变化。通过探索不同大都市在大流行期间和之后的停车政策，研究了停车需求的转变。检查了与墨尔本城市停车相关的详细物联网（IoT）数据，例如传感器和设备。使用解释性数据分析深入研究了 2019 年（3 月 16 日至 5 月 26 日）和 2020 年（3 月 16 日至 5 月 26 日）的实证数据，以展示从区域到区域的需求和平均停车时间的变化。结果表明，Docklands、Queensbery、Southbanks、Titles 和 Princess Theatre 区域的实验区域的车辆存在百分比变化分别减少了 29.2%、36.3%、37.7%、23.7%和 40.9%。此外，Princess Theatre 区域、Lonsdale Street、Exhibition Street、Spring Street 和 Little Bourke Street 路边停车位的街道层面分析表明，车辆存在百分比变化分别减少了 38.7%、56.4%、12.6%和 35.1%。总之，讨论了未来潜在的决策制定框架，这些框架可以为制定大流行期间的防疫控制政策，特别是停车法规提供进一步的指导。
