# Road Passenger Load Probability Prediction and Path Optimization Based on Taxi Trajectory Big Data
## 5 Experimental Results
### Mining of Passenger Search Start and End Points  
This paper analyzes taxi trajectory data for the morning peak, noon peak, and evening peak on August 18 (a weekday) and August 23 (a non-working day) using the grid-optimized DBSCAN clustering algorithm. The goal is to identify recommended passenger search points for each time period. The specific scheme information is shown in Figures 7 and 8. From Figures 7 and 8, it can be analyzed that the following three phenomena exist in the hot spots of taxi passengers in the morning peak:  
1. During the morning rush hour, loading points are concentrated in Xindu and Wuhou districts;
2. During the morning peak hour, the highest number of passengers carried on weekdays was at Exit C of Chengdu North Railway Station Metro Station, the highest number of passengers carried on non-weekdays was at Xinnanmen Metro Station, and the number of passengers carried by taxis on non-weekdays was significantly higher than  
Figure 7: Specific points recommended for morning peak seeking on August 18 (weekdays). that on weekdays, with a difference of 145 passengers between the two peaks in the morning peak;
3. During the morning peak hour, weekday loading points come from a complex source, originating from transportation hubs, commercial districts, and hospitals, and non-weekday loading points are generally at transportation hubs. From Figures 9 and 10, we can analyze the following three phenomena in the hot spots of taxi passengers in the afternoon peak:  
1. During the midday peak hour, loading points are concentrated in Jinjiang, Wuhou, and Xindu districts;
2. During the midday peak hour, the highest number of passengers carried on weekdays was at the Commercial Grounds Shopping Center, the highest number of passengers carried on non-weekdays was at the North Train Station, and there was almost no difference in the highest point of the midday peak between weekdays and non-weekdays;
3. During the midday peak hour, unlike the morning peak hour, the loading points are concentrated at the entrances of commercial districts and scenic spots, and the rest are at the transportation hubs, both on weekdays and non-weekdays. Based on the analysis of passenger hotspots during morning, noon, and evening peak hours on both weekdays and non-working days, the following four conclusions can be drawn:  
1. Regardless of whether it is the morning, noon, or evening peak hours, passenger pick-up points are concentrated in Wuhou District, Jinjiang District, and Xindu District;
2. During weekdays, the types of passenger pick-up points during morning and evening peak hours are diverse, including locations such as hospital entrances, transportation  
Figure 8: Specific points recommended for morning peak seeking on August 23 (non-working days). Figure 9: Specific points recommended for midday peak passenger-seeking on August 18 (weekday). hubs, and commercial areas. During non-working days, the noon and evening peak pick-up points are significantly concentrated in commercial areas;
3. Whether on weekdays or non-working days, Chengdu Shuangliu International Airport T2 Terminal and Chengdu North Railway Station consistently rank among the top in terms of taxi passenger numbers;
4. The number of taxi passengers on non-working days is approximately 22% higher than on weekdays. Taxi drivers can adjust their operating hours accordingly to optimize their service during these periods. Taking the recommended area for taxis in the morning peak on August 18 as an example, the three basic indicators of the recommended area for taxi passenger search are shown in Table 3.  
Based on the entropy weight-TOPSIS method, the ranking results of recommended taxi areas during the morning rush hour on 18 August are as follows: Shuangliu Airport, Provincial Hospital, Evergrande Plaza, Chengdu North Railway Station, Sichuan University, and RT-Mart.