Sustainable response strategy for COVID-19: Pandemic zoning with urban multimodal transport data.

In the post-COVID-19 era, the pandemic response is increasingly difficult and entails a high cost to society. Existing pandemic control methods, such as lockdowns, greatly affect residents' normal lives. This paper proposes a pandemic control method, consisting of the scientific delineation of urban areas based on multimodal transportation data. An improved Leiden method based on the gravity model is used to construct a preliminary zoning scheme, which is then modified by spatial constraints. The modularity index demonstrates the suitability of this method for community detection. This method can minimize cut-off traffic flows between pandemic control areas. The results show that only 24.8% of travel links are disrupted using our method, which could reduce both the impact of pandemic control on the daily life of residents and its cost. These findings can help develop sustainable strategies and proposals for effective pandemic response.

Exploring year-to-year changes in station-based bike sharing commuter behaviors with smart card data

Station-based bike sharing (SBBS) not only provides commuters with direct "door-to-door" trips, but also plays a vital role in addressing the "first/last mile" challenges for public transportation system. However, there is a lack of research into portraying year-to-year changes in SBBS commuter behaviors. With five-year (from 2016 to 2020) SBBS smart card data collected in Nanjing, China, a longitudinal analysis is performed in this study to trace yearly dynamics of commuter behaviors at an individual level. We identify two sorts of SBBS commuters (i.e., SBBS-alone and SBBS-metro commuters) based on users' spatial-temporal travel regularities. The paper finds that (i) the number of SBBS users presented a considerable fluctuation trend over a five-year span, while the proportion of SBBS commuters stabilized at an equilibrium level;(ii) the COVID-19 outbreak accelerated the decline in the proportion of female and young SBBS commuters;(iii) most SBBS commuters were recorded for only one year out of five, while the share of commuters who used SBBS for four years or more is tiny, < 5%;(iv) the trip duration of SBBS-alone commuters was significantly longer than that of SBBS-metro commuters, and both showed some increase during the COVID-19 pandemic;(v) the number of non-loop trip chains was dramatically higher than that of loop trip chains, which is more prominent among SBBS-metro commuters. Our findings could provide valuable insights into the behavioral dynamics of SBBS commuters and offer recommendations on how policy makers and transportation planners could respond to these precipitate changes. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Minimizing fleet size and improving vehicle allocation of shared mobility under future uncertainty: A case study of bike sharing

As a rapidly expanding type of shared mobility, bike sharing is facing severe challenges of bike over-supply and demand fluctuation in many Chinese cities. In this paper, a large-scale method is developed to determine the minimum fleet size under future demand uncertainty, which is applied in a case study with millions of bike sharing trips in Nanjing. The findings show that if future uncertainty is not considered, more than 12% of trip demands may not be satisfied. Nevertheless, the proposed algorithm for minimizing fleet size based on historical trip data is effective in handling future uncertainty. For a bike sharing system, supplying 14.5% of the original fleet could be sufficient to meet 96.8% of trip demands. Meanwhile, the results suggest a unified platform that integrates multiple companies can significantly reduce the total fleet size by 44.6%. Moreover, in view of the Coronavirus Disease 2019 (COVID-19) pandemic, this paper proposes a contact delay policy that maintains a suitable usage interval, which results in increased bike amount requirements. These findings provide useful insights for improving resource efficiency and operational services in shared mobility applications.

Exploring year-to-year changes in station-based bike sharing commuter behaviors with smart card data

Station-based bike sharing (SBBS) not only provides commuters with direct “door-to-door” trips, but also plays a vital role in addressing the “first/last mile” challenges for public transportation system. However, there is a lack of research into portraying year-to-year changes in SBBS commuter behaviors. With five-year (from 2016 to 2020) SBBS smart card data collected in Nanjing, China, a longitudinal analysis is performed in this study to trace yearly dynamics of commuter behaviors at an individual level. We identify two sorts of SBBS commuters (i.e., SBBS-alone and SBBS-metro commuters) based on users’ spatial-temporal travel regularities. The paper finds that (i) the number of SBBS users presented a considerable fluctuation trend over a five-year span, while the proportion of SBBS commuters stabilized at an equilibrium level;(ii) the COVID-19 outbreak accelerated the decline in the proportion of female and young SBBS commuters;(iii) most SBBS commuters were recorded for only one year out of five, while the share of commuters who used SBBS for four years or more is tiny, <5%;(iv) the trip duration of SBBS-alone commuters was significantly longer than that of SBBS-metro commuters, and both showed some increase during the COVID-19 pandemic;(v) the number of non-loop trip chains was dramatically higher than that of loop trip chains, which is more prominent among SBBS-metro commuters. Our findings could provide valuable insights into the behavioral dynamics of SBBS commuters and offer recommendations on how policy makers and transportation planners could respond to these precipitate changes.

Should bike-sharing continue operating during the COVID-19 pandemic? Empirical findings from Nanjing, China.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has triggered a worldwide outbreak of pandemic, and transportation services have played a key role in coronavirus transmission. Although not crowded in a confined space like a bus or a metro car, bike-sharing users are exposed to the bike surface and take the transmission risk. During the COVID-19 pandemic, how to meet user demand and avoid virus spreading has become an important issue for bike-sharing. METHODS: Based on the trip data of bike-sharing in Nanjing, China, this study analyzes the travel demand and operation management before and after the pandemic outbreak from the perspectives of stations, users, and bikes. Semi-logarithmic difference-in-differences model, visualization methods, and statistic indexes are applied to explore the transportation service and risk prevention of bike-sharing during the pandemic. RESULTS: Pandemic control strategies sharply reduced user demand, and commuting trips decreased more significantly. Some stations around health and religious places become more important. Men and older adults may be more dependent on bike-sharing systems. The declined trips reduce user contacts and transmission risk. Central urban areas have more user close contacts and higher transmission risk than suburban areas. Besides, a new concept of user distancing is proposed to decrease transmission risk and the number of idle bikes. CONCLUSIONS: This paper is the first research focusing on both user demand and transmission risk of bike-sharing during the COVID-19 pandemic. This study evaluates the mobility role of bike-sharing during the COVID-19 pandemic, and also provides insights into curbing the viral transmission within the city.