This work attempts to understand how a customized bus(CB)operator decides to open or close a CB line.We look into the changes in the operation status of CB lines(i.e.reopening and closure)from one of the largest CB op...This work attempts to understand how a customized bus(CB)operator decides to open or close a CB line.We look into the changes in the operation status of CB lines(i.e.reopening and closure)from one of the largest CB operators in Shanghai,China,with a 22-month con secutive observation ranging from January 2019 to October 2020.As all CB services were totally suspended at the beginning of 2020 due to the COVID-19 travel restriction and then gradually recovered in March 2020,we utilize this study period as a naturalistic observa tion experiment to investigate the changes in the operation status of each CB line before and after the travel restriction.Using the operation status at each month as the binary alternatives,the mixed logit models and the tree-based models with explainable machine learning techniques are respectively adopted to explore the factors that influence the decision-making process.The findings from both types of models are in general consistent.The results show that the characteristics of each CB line including the ridership,the length of the line,the closeness to charging stations,and the overlap of CB lines significantly impact the decisions.In addition,the land-use types around the CB stops and the market competition from alternative travel modes also play a key role in making the decisions.展开更多
基金This work is supported by the National Natural Science Foundation of China(Grant Nos.52272321,71901164,52272335)the Fundamental Research Funds for the Central Universities.
文摘This work attempts to understand how a customized bus(CB)operator decides to open or close a CB line.We look into the changes in the operation status of CB lines(i.e.reopening and closure)from one of the largest CB operators in Shanghai,China,with a 22-month con secutive observation ranging from January 2019 to October 2020.As all CB services were totally suspended at the beginning of 2020 due to the COVID-19 travel restriction and then gradually recovered in March 2020,we utilize this study period as a naturalistic observa tion experiment to investigate the changes in the operation status of each CB line before and after the travel restriction.Using the operation status at each month as the binary alternatives,the mixed logit models and the tree-based models with explainable machine learning techniques are respectively adopted to explore the factors that influence the decision-making process.The findings from both types of models are in general consistent.The results show that the characteristics of each CB line including the ridership,the length of the line,the closeness to charging stations,and the overlap of CB lines significantly impact the decisions.In addition,the land-use types around the CB stops and the market competition from alternative travel modes also play a key role in making the decisions.
