ABSTRACT
The outbreak of COVID-19 has made a profound impact on mobility, especially for public transport users. Extensive research has been conducted on the change of travel patterns in major cities where public transport systems have been well developed and heavily used. However, in small cities, the public transport network is relatively sparse, especially in suburban areas, which makes the corresponding travel patterns differ from those in major cities. Therefore, proper investigation of the public transport usage in such small cities is still needed, especially under the COVID-19 impact. This paper aims to reveal the change of public transport users' travel patterns based on a comparative study of public transport usage Pre-COVID and during the COVID-19 period. The Illawarra, a coastal region close to Sydney in Australia is used as a case study. Smart card data is used to reveal relevant changes in both intraregion (in the Illawarra) and inter-region (between the Illawarra and Sydney) travels in consideration of heterogeneous user groups. The results show a significant decrease (around 47%) in public transport ridership by both train and bus. However, compared to intra-region ridership, the inter-region trips by train drop much more (around 62%). Moreover, heterogeneous age group passengers show different changes after the COVID-19 outbreak. The research findings are expected to provide valuable suggestions for policy making and public transport service adjustment when a similar crisis occurs again. © 2022 IEEE.
ABSTRACT
This paper proposes the Susceptible-exposed of Small-world Network Model (SSEM) by combining the Susceptible-Exposed-Infectious-Recovered (SEIR) model with the Small-world Network (SN) model. The scenarios of COVID-19 propagation in urban public transport network was set by the specific model parameters. A study area, Huicheng District, Huizhou City, Guangdong Province, China, was selected to estimate the temporal and spatial distribution characteristics of COVID-19 within 12 hours based on SSEM. The results show that, without taking protective measures, if the two infectious source were in a bus, after 12 hours, 324 bus stations, 762 infected people and 68.85km2 were covered in the study area. The results of this study will provide a reference for the future study of COVID-19 virus transmission mechanism in the small enclosed environment. © 2021 IEEE.
ABSTRACT
The outbreak of COVID-19 in 2020 greatly impacted China's transportation industry. This paper aims to analyze this impact and the indispensable role of public transport control measures in preventing the spread of the epidemic. The impact of SARS and COVID-19 was compared. Taking Hebei Province as an example, the impact of the epidemic on the public transport industry was analyzed. The information of Jincheng public transport network and bus IC card data were selected for analysis. The parameters of bus network density and bus line repetition coefficient were calculated. The number of bus departures of each line before and after Jincheng epidemic was counted. Based on the data of bus IC card, the dynamic network of passenger contact was constructed, and the passenger contact network diagram was drawn. The analysis results can inform and enable urban public transport departments to take control measures when public health emergencies occur. © 2021 CICTP 2021: Advanced Transportation, Enhanced Connection - Proceedings of the 21st COTA International Conference of Transportation Professionals. All rights reserved.