Dataset for: Interactive Effects of Initial Trust and Warning Type on Takeover Performance in Conditionally Automated Driving: An Information Processing Perspective

This dataset contains the experimental data and Data Dictionary supporting the manuscript titled "Interactive Effects of Initial Trust and Warning Type on Takeover Performance in Conditionally Automated Driving: An Information Processing Perspective". The data were generated from a 2×2 within-subjects driving simulator experiment investigating the effects of warning type (single-stage vs. two-stage) and initial trust (low vs. high) on takeover performance, eye-tracking measures, and subjective evaluations in conditionally automated driving. The dataset is structured within a single multi-sheet .xlsx file, comprising data from 24 valid participants. It explicitly focuses on the 288 Type C critical takeover events extracted for the core statistical analyses (24 participants × 4 blocks × 3 events per block). The workbook is organized into five specific sheets: 1. Data_Dictionary: Comprehensive operational definitions, value labels, and units for all variables. 2. Main_Dataset: The consolidated event-level data matrix encompassing Demographics, Takeover Performance (Takeover Success, TRT, Min TTC), and phase-divided Eye-tracking Measures (TTFF_Post, PFD_Baseline, PFD_Pre, PFD_Post, Delta_PD_Pre, Delta_PD_Post). 3-5. Pre_Trust_Score, Post_Trust_Score, and Workload_TLX: Three detailed sheets containing the full item-level data and sub-dimensional scores for the subjective evaluations. Access Note: To ensure participant privacy and adhere to the ethical guidelines approved by the Ethics Committee of Beihang University, the raw datasets containing individual eye-tracking and human factors data are under restricted access. De-identified data are available from the corresponding author upon reasonable request strictly for academic verification or replication purposes.