## 3 Study Site, Data, and Analysis  
The data analyzed are 5 min aggregated traffic data collected using a microwave radar sensor on an on-ramp bottleneck at the Burapha Withi Expressway in Bangkok, Thailand. The expressway is an elevated limited-access highway. This paper considers the southbound direction at Sta. 16 + 600I to 21 + 150I. This on-ramp was selected because of its proximity to the Automatic Weather Station (AWS) in the area, which is around 3 km away from Sta. 16 + 600I. This consideration will be important to the analysis since this paper relates precipitation rate to traffic flow dynamics. The activation of the bottleneck is measured 650 m from it, and the queue discharge rate is measured using the sensor at 21 + 150I, which is 4550 m away downstream. This distance ensures that there is no external cause of congestion further downstream and that the cause of the breakdown will be endogenous. This site occasionally becomes an active bottleneck where the queue discharge rate is not affected by downstream traffic conditions. This is an important consideration for the phenomenon to be considered a capacity drop. The study area diagram is shown in Figure 1.  
Data for analysis are collected for the whole year of 2022. This includes days with and without precipitation. Data is representative of clear, light, medium, and heavy rainfall conditions. The characteristics of the bottleneck are identified by comparing the upstream  
Figure 1: On-ramp bottleneck data site, Burapha Withi Expressway, Bangkok, Thailand. and downstream location speeds. The bottleneck is considered active when the upstream speeds dramatically drop while the downstream remains at free-flow speed. After this, the activation time, bottleneck duration, and traffic states can be identified. Classifications are free-flow, transition to bottleneck, bottleneck, and recovery from the bottleneck. The bottleneck period is when the upstream speed is less than 70 kph, and the downstream speed is sustained at more than 80 kph for at least 15 min. After verifying that the on-ramp is an active bottleneck, cumulative vehicle count curves measured at the data locations plotted in oblique or slanted coordinates were used to determine the capacity drop. The vertical displacements represent vehicle accumulations. In the oblique coordinate system, the cumulative counts are plotted against time. However, in order for the change in slope to be more noticeable, a background flow multiplied by each time interval is subtracted from the cumulative counts. This is a popular approach to observing the capacity drop at upstream and downstream locations near the bottleneck based on the work of [PERSON] [31], who used assumptions about wave motion to predict the features of cumulative vehicle arrival curves. The methodology was improved by [PERSON] and [PERSON] [7] by rescaling the N-curve. Capacity and queue discharge rates can be measured through the oblique cumulative curve downstream. The change in slope indicates the change in flow. At the activation time, density is then measured at the location near the bottleneck to show the density triggering the capacity drop. The discharge before and after the capacity drop is then measured from the slanted cumulative curve. This is also shown quantitatively in the data as the maximum flow sustained for at least 10 min before and after bottleneck activation. The capacity drop is then calculated based on the difference between the two discharges. The speed in congestion is calculated as the average of speeds detected at the upstream location near the bottleneck during its activation. Shown in Figure 2 is the traffic data analysis for 1 June 2022, which is shown as an example of typical data analysis. The same analysis was done for all the other days. The mechanism of the capacity drop began when the upstream and downstream oblique cumulative curves started diverging (Figure 2a).