Development of a personal computer-based secondary task procedure as a surrogate for a driving simulator
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Summary
This research addresses the high cost and limited availability of driving simulators for evaluating driver reactions to traffic control devices, specifically Changeable Message Signs (CMS). While driving simulators offer realistic conditions, they are expensive and immobile, restricting sample sizes and geographic reach. Conversely, personal computer-based studies are cheaper and more accessible but often lack the secondary mental workload inherent in actual driving, leading to skepticism about their validity. The study aimed to develop and validate a Personal Computer-Based Study Procedure (PCSP) that incorporates a secondary task to mimic driving workload, determining if it could yield comparable results to a fixed-base driving simulator regarding CMS message reading times and comprehension. The study involved 126 subjects who met specific driving and vision criteria, with demographics matched to Texas drivers. Participants were tested in both a fixed-base driving simulator and the PCSP. In the PCSP, subjects viewed CMS messages while performing a secondary task: deactivating randomly appearing buttons on a screen. Three workload levels were tested: no secondary task, 0.625 buttons per second, and 0.909 buttons per second. In the simulator, subjects performed a car-following task. Ten CMS messages across five formats (including flashing, static, and numeric content) were presented in self-paced and fixed-time (8.4 seconds) conditions. Reading times and comprehension were measured and statistically compared between the two methods using z-tests, t-tests, and tests of proportions. The analysis revealed that the PCSP generally produced conclusions consistent with the driving simulator. For average reading times, the PCSP matched simulator conclusions for all message formats across all three workload levels, with only two minor exceptions. Specifically, the PCSP with no secondary task yielded average reading time differences statistically indistinguishable from the simulator. However, at higher workload levels (0.625 and 0.909 buttons/second), some individual message reading times differed significantly, particularly for complex two-phase messages, where subjects sometimes cut short viewing in the PCSP. Regarding comprehension, no significant differences were found for most message sets. Significant discrepancies appeared only for specific two-phase messages and static messages under certain workload conditions, suggesting the PCSP may not fully replicate simulator results for complex information processing. The study concludes that the PCSP is a viable, cost-effective surrogate for driving simulators when evaluating CMS messages. The version with no secondary task or the 0.625 buttons/second rate produced the fewest statistical differences from the simulator. Although minor discrepancies existed for complex messages, the overall findings indicate that researchers can use the PCSP to test larger samples efficiently without sacrificing the validity of conclusions regarding reading time and general comprehension. This validates the use of computer-based secondary tasks to approximate the cognitive load of driving in laboratory settings.
Key finding
The personal computer-based study procedure produced essentially the same conclusions regarding average reading times for changeable message sign messages as the driving simulator across all tested secondary workload levels.
Methodology
mixed_methods
Sample size: 126
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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- Empirical Findings: behavioral performance data
- Methodological Resource: tool software, measurement protocol