新冠肺炎时代,交通方式从公共交通转向共享单车:骑行回归常态

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-01-01 DOI:10.1016/j.jpubtr.2023.100071
Zoi Christoforou , Anna Mariam Psarrou Kalakoni , Christos Gioldasis
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引用次数: 0

摘要

疫情导致公共交通工具使用量减少,许多乘客认为他们已经从公共交通工具转向共享单车。我们提出了一种新的方法来量化这种转变,并阐明了新偏好的因果因素以及它们继续存在的可能性。第一次短期模态内分析揭示了出行量和持续时间与COVID-19政策措施之间的重要相关性。COVID-19大大减少了所有出行,但公共交通受到的打击更大,迄今尚未恢复。在大流行高峰期间,共享单车出行时间延长。然后,我们进行了第二次中期、分类和多式联运分析,以确定从公共交通转向骑自行车的潜在原因。Logit模型是在伦敦和华盛顿特区的经验客流量数据上指定的。结果表明,在COVID-19下,某些前因素(如天气和天气类型、旅行目的)仍然有影响。此外,我们发现面部遮盖义务是恢复公众对公共交通信心的关键因素。相反,简单的遮住脸的建议似乎会阻碍公共交通的使用,而有利于骑自行车。
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Mode shifts from public transport to bike-sharing in the era of COVID-19: Riding back to normality

The pandemic led to the decrease of public transport use, which many passengers believed to have shifted from public transport to bike-sharing. We propose a novel methodology to quantify this shift and shed light on the causal factors of new preferences as well as the likelihood of their continuation. A first short-term intramodal analysis reveals important correlations between trip volumes and durations on the one hand, and COVID-19 policy measures on the other hand. COVID-19 significantly reduced all trips but public transport was hit harder and has not recovered so far. Shared-bike trip durations were extended during pandemic peaks. Then, we perform a second medium-term, disaggregate, and intermodal analysis to identify potential reasons explaining the shift from public transport to cycling. Logit models are specified on empirical ridership data from London and Washington DC. Results indicate that certain pre-covid factors (such as weather and type of day, travel purpose) remain influential under COVID-19. Also, we find facial covering obligation to be a key element in restoring public confidence towards public transport. Simple face covering recommendations seem, instead, to discourage public transport usage and play in favor of cycling.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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