The present study aims to reveal the contributing factors for train delays in Tokyo metropolitan area by conducting statistical analyses, focusing on passenger trains, and using a variety of information by including d...The present study aims to reveal the contributing factors for train delays in Tokyo metropolitan area by conducting statistical analyses, focusing on passenger trains, and using a variety of information by including data concerning train cars, stations, passengers, tracks and working timetables as explanatory variables. The present study conducted 2 types of statistical analyses including the standard multiple regression analysis and the logistic regression analysis by setting “average delay time” which indicates the quantitative conditions of delays, and “occurrence of delays” which indicates the qualitative condition, as objective variables. According to the results of the logistic regression analysis, the possibility of direct operations increasing the delay occurrence rate was quantitatively indicated. Therefore, direct operations are regarded as a contributing factor for train delays concerning metropolitan areas in recent years. Additionally, it was confirmed that the concentration of demand on terminal stations is also a contributing factor for train delays. On the other hand, it is certain that direct operations contribute to improving the convenience of passengers as well as the operational efficiency of train cars. Therefore, it would be ideal to resolve delays by easing the concentration of demands which may be accomplished by recommending off-peak commuting as well as adjustments to the working timetables.展开更多
The present study aims to conduct 2 types of statistical analysis to reveal the impact of the spread of COVID-19 on train delays by comparing the potential contributing factors before, during and after the outbreak of...The present study aims to conduct 2 types of statistical analysis to reveal the impact of the spread of COVID-19 on train delays by comparing the potential contributing factors before, during and after the outbreak of the virus in the metropolitan train lines in Japan. First of all, the result of the present study clearly revealed the changes in contributing factors for train delays caused by the spread of COVID-19. Specifically, the contributing factors for train delays changed due to the decrease of passengers by the effect of the outbreak of the virus. Additionally, though large terminal stations were considered to be a major contributing factor in causing and increasing train delays in the past, this was not the case after the spread of COVID-19. Therefore, under such conditions, it is more effective to make improvements in small to medium stations and tracks rather than terminal stations. Furthermore, as the decrease in passengers also decreased train delays in commuter lines going to the suburbs due to the spread of COVID-19, the contributing factor for such lines is the excessive number of passengers. Therefore, as for countermeasures for train delays after the effects of COVID-19, it is necessary to disperse passengers in order to avoid passengers concentrating in the same time zones and train lines.展开更多
文摘The present study aims to reveal the contributing factors for train delays in Tokyo metropolitan area by conducting statistical analyses, focusing on passenger trains, and using a variety of information by including data concerning train cars, stations, passengers, tracks and working timetables as explanatory variables. The present study conducted 2 types of statistical analyses including the standard multiple regression analysis and the logistic regression analysis by setting “average delay time” which indicates the quantitative conditions of delays, and “occurrence of delays” which indicates the qualitative condition, as objective variables. According to the results of the logistic regression analysis, the possibility of direct operations increasing the delay occurrence rate was quantitatively indicated. Therefore, direct operations are regarded as a contributing factor for train delays concerning metropolitan areas in recent years. Additionally, it was confirmed that the concentration of demand on terminal stations is also a contributing factor for train delays. On the other hand, it is certain that direct operations contribute to improving the convenience of passengers as well as the operational efficiency of train cars. Therefore, it would be ideal to resolve delays by easing the concentration of demands which may be accomplished by recommending off-peak commuting as well as adjustments to the working timetables.
文摘The present study aims to conduct 2 types of statistical analysis to reveal the impact of the spread of COVID-19 on train delays by comparing the potential contributing factors before, during and after the outbreak of the virus in the metropolitan train lines in Japan. First of all, the result of the present study clearly revealed the changes in contributing factors for train delays caused by the spread of COVID-19. Specifically, the contributing factors for train delays changed due to the decrease of passengers by the effect of the outbreak of the virus. Additionally, though large terminal stations were considered to be a major contributing factor in causing and increasing train delays in the past, this was not the case after the spread of COVID-19. Therefore, under such conditions, it is more effective to make improvements in small to medium stations and tracks rather than terminal stations. Furthermore, as the decrease in passengers also decreased train delays in commuter lines going to the suburbs due to the spread of COVID-19, the contributing factor for such lines is the excessive number of passengers. Therefore, as for countermeasures for train delays after the effects of COVID-19, it is necessary to disperse passengers in order to avoid passengers concentrating in the same time zones and train lines.
