Update README.md

Supplement the details of the experimental scene

README.md

@@ -23,9 +23,43 @@ size_categories:
 
 # DATAD: Driver Attention in Takeover of Autonomous Driving
 
+## Dataset Overview
+
 This dataset provides **multimodal recordings** for analyzing driver attention during **takeover scenarios in autonomous driving**.  
-It includes **gaze-object interactions, feature vectors, and image segmentation data**.  
-The dataset supports research in **driver monitoring, gaze estimation, takeover performance, and semantic scene understanding**.
+It includes **gaze–object annotations, per-frame feature vectors, and instance segmentation outputs**, supporting research in **driver monitoring, gaze estimation, takeover performance, and semantic scene understanding**.
+
+## Data Organization and Participants
+
+Data are organized **per participant**, with each participant’s data compressed and uploaded individually in **7Z format**.
+
+- **Tester1–Tester10**: university students with driving experience  
+- **Tester11–Tester30**: experienced drivers (ride-hailing drivers)
+
+The two participant groups were exposed to **different scenario designs**.
+
+
+## Scenario Design
+### Tester1–Tester10 (Student Drivers)
+Two major categories of **explicit high-risk scenarios**, each containing:
+- **One primary risk**
+- **One secondary risk**
+
+Scenario categories:
+1. **Road construction ahead**
+2. **Sudden intrusion of non-motorized vehicles**
+
+Each category includes multiple concrete scenarios generated by **varying background vehicle behaviors**.
+
+
+### Tester11–Tester30 (Experienced Drivers)
+**Progressive risk scenarios** with latent and gradually emerging hazards, divided into two major categories:
+
+1. **Right-side vehicle squeezing lane change + left-side non-motorized sudden appearance**
+2. **Left-side non-motorized vehicle intrusion + front traffic accident**
+
+Similarly, each category is instantiated into multiple scenarios by **adjusting background traffic behaviors**.
+
+Overall, the dataset enables comparative analysis of **driver attention and takeover behavior across driver experience levels and scenario complexities**.
 
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@@ -123,3 +157,5 @@ These files provide **low-level driving signals, ego vehicle states, and scene-l
 - `Gaze_object_output/` (gaze–object annotations)
 - `Tester*_IS/` (instance segmentation outputs)
 
+
+