Examining the Association Between Bus Transit Reliability and Ridership
Analytics
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Abstract
The road infrastructure has not been developed at the rate of growing travel demand in many cities in the United States, mainly due to space and resource constraints. Practitioners are exploring means to increase public transportation ridership with economically efficient investment plans to cater the travel demand, reduce congestion, and contribute to sustainability. Despite these ongoing efforts, recent statistics indicate that public transportation ridership has decreased in many cities in the United States, and bus ridership alone fell by 5% in 2017 compared to the previous year. There is a need to research and identify factors that encourage the use of public transportation systems over other modes of transportation.The research explaining the relationship between bus transit reliability and ridership is limited. The reliability of a bus transit system by bus stop type, time of the day, day of the week, and direction of travel may influence the ridership. In other words, it is not clear how bus transit reliability influences the ridership temporally and spatially at a bus stop level. Therefore, this research aims to examine the association between bus transit reliability and ridership from a bus user perspective at a bus stop level. The objectives of this research are: 1) to identify and better understand the bus transit reliability performance measure, 2) to analyze the relationship between bus transit reliability and ridership, by considering the time of the day, day of the week, and direction of travel, and 3) to research the effect of bus stop type (for example, transit center, bus stop near a light rail transit [LRT] station, transit centers near LRT etc.,) on bus transit reliability and ridership relationships. The city of Charlotte in North Carolina was considered as the study area. All data pertaining to bus transit reliability and ridership was gathered from the Charlotte Area Transit System (CATS) for the year 2017. The data was processed to compute bus transit reliability and ridership at the bus stop level. A total of 394 bus stops were considered for the analysis. The on-time performance (OTP) percentage was considered as the bus transit reliability measure while the average number of boarding was considered as ridership. The OTP percentages were computed comparing the scheduled and actual departure times (-1 to +5 min and -1 to 3min). In other words, the bus transit reliability threshold is set using an acceptable range from 1 minute early to 5 minutes late or 1 minute early to 3 minutes late. The results from the D’Agostino’s Pearson K^2 test indicate that the data is normally distributed at a 95% confidence level. Therefore, the relationship between the bus transit reliability and ridership was evaluated using Pearson correlation analysis. The Pearson correlation analysis was carried out at four levels: considering the day of the week, time of the day, direction of travel, and bus stop type. The results for a typical service day indicated that a bus transit user boards the bus if it departs on-time, irrespective of whether the bus arrives on-time or not. Four different peak hours of the day were considered and analyzed to better understand this association over different times of the day. The results showed that the association between bus transit reliability and ridership is more significant in the morning and night-time hours, accounting for the work trips made by the bus transit users. Interpreting the association based on the trip purpose paved the way to explore the relationship between bus transit reliability and ridership by considering the direction of travel. A high positive correlation between bus transit reliability and ridership was observed in the morning peak and night-time hours. This indicates the high reliability requirement for work trips in the inbound direction travel (morning peak hour) and outbound direction travel (nighttime hour). The nature of the relationship between the bus transit and ridership still remained unclear when intermodal effects like the LRT was considered. Reliability certainly is one of the most important service characteristics to transit customers, while operating in coordination with the other transit service like LRT is linked with customer satisfaction. The bus stops were segregated based on their spatial location from the LRT stations. The results based on the bus stop type indicated a higher positive correlation between bus transit reliability and ridership at bus stops near LRT stations than bus stops located far away from the LRT station. Transit centers that serve as transfer stops have high bus transit reliability, which attracts more people to use the bus transit system. The Pearson correlation analysis based on the direction of travel and bus stop type indicated a more significant association between the bus transit reliability and ridership at bus stops near LRT and in the outbound direction of travel. The methodological framework illustrated in this research helps understand the influence of bus transit reliability on ridership at a bus stop level from a transit user perspective. The findings from this research help practitioners and professionals better plan, design, and operate the transit system in an urban area and assess to what extent a reliable transit system influences its ridership.