# Estimating Destination of Bus Trips Considering Trip Type Characteristics
## 5 Results
### Estimated Results of Destination by Trip Type Characteristics
Although the percentage of the non-continuous, recurrent travels in the total bus trips is 6.34%, which is not high, this trip type can be utilized as a supplementary method to estimate the alighting stops more effectively for disconnected trips by regularity. Furthermore, because this trip type indicates better results when it is compared to the non-recurrent travels in terms of accuracy, it is appropriate to apply it to Stage 2. For the non-continuous, non-recurrent travels, the missing alighting stops are estimated based on the past travel history (weekdays and weekends are distinguished) for each card ID. Based on the fact that the passenger's residence and major destination do not change much, even if the passenger does not travel to the destination repeatedly according to the travel history of each person, it is confirmed that this trip type can be utilized to supplement the alighting stop estimation method. However, when the error between the estimated and actual alighting stops is less than 1 km, the accuracy is 66.53%, which is low compared to that of the recurrent travels. Furthermore, among the non-continuous, non-recurrent travels, 6.18% accounted for the case where the alighting stops could not be estimated, and the estimation is impossible if there is no past travel history. Finally, the route pattern-applied alighting stop estimation is performed when the estimation is impossible in Stages 1-3 performed earlier. According to the alighting stop estimation results, 12.32% of the estimated stops are similar to the actual alighting stops, and 44.92% accounts for the case where the distance (error) between the estimated and actual alighting stops is less than 1 km. The accuracy is relatively low because route patterns, not each person's patterns, are applied. Upon examining the accuracy (less than 1 km) of the alighting estimation for each stage, we found that the accuracy for the continuous travels was the highest (94.39%), and that of the results utilizing route patterns was the lowest (44.92%). This study aims to ensure that more complete information is reflected when monitoring operations and making decisions by building a public transportation dataset that can be utilized in the field. Accordingly, we have designed a methodology that ensures a 100% valid tag rate by applying the route patterns in the last stage. Although the accuracy is low in the case of route patterns, there will be no challenge in utilizing them in the actual field because the composition ratio is relatively low at 6.18%. Figure 4: Result of destination estimation accuracy. According to the analysis on the alighting stop estimation results for each day of the week, the accuracy is low in the case of weekends (Saturday/Sunday) than in the case of weekdays. When the accuracy is examined for each stage, we find that there is no significant difference between the weekdays and the weekends in the cases of continuous travels and non-continuous, recurrent travels. However, in the cases of the non-continuous, non-recurrent travels and the route patterns, the accuracy is 2.5-5.0% lower on the weekends compared to the weekdays. The accuracy of the pattern-based estimation method is relatively low because the variability of the weekend trip patterns is relatively high.