Driver’s Behavior and Mental Workload of Self-Driving Vehicle Following Behind Speed-Limited Autonomous Vehicle
DOI: 10.1299/jsmetld.2019.28.2006
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Summary
This study investigates the driving behavior and mental workload of human drivers operating manual vehicles while following speed-limited autonomous vehicles. The research is motivated by the anticipated transitional period in which autonomous and conventional vehicles will share roadways. Specifically, it addresses the potential psychological burden and safety risks when a driver, wishing to travel at higher speeds, is forced to follow an autonomous vehicle that strictly adheres to lower speed limits. Previous research indicates that such "rush driving" scenarios can impair cognitive judgment, increase collision risks, and distort distance and time perception. This paper aims to clarify the specific characteristics of driving behavior and mental load under these conditions using a driving simulator. The experimental design utilized a driving simulator featuring a 6 km, two-lane straight road. Participants drove a manual vehicle at a base speed of 80 km/h, encountering two groups of four autonomous vehicles traveling at either 40 km/h or 60 km/h. To induce realistic time pressure and mental workload, participants were instructed to reach the destination as quickly as possible and were offered a reward for completing specific trials within a time limit, though the specific conditions for the reward were not disclosed to prevent strategic disengagement. The study manipulated the speed of rear-side vehicles in the passing lane at 90, 110, or 120 km/h, or included a condition with no rear-side vehicles, resulting in eight distinct traffic scenarios. Data collection focused on two primary metrics: collision risk and mental workload. Collision risk was assessed using Time to Collision (TCC), measuring the safety margin during overtaking maneuvers. Mental workload was evaluated using the NASA Task Load Index (NASA-TLX), a subjective assessment tool comprising six dimensions: mental demand, physical demand, temporal demand, performance, effort, and frustration. Participants rated these dimensions on a scale of 0 to 100 and performed pairwise comparisons to determine the weight of each factor, allowing for a comprehensive calculation of overall task load. The paper outlines the methodology and experimental setup for this investigation but does not present the final results or statistical analysis within the provided text. The authors state that the experimental results and discussion were intended to be reported via poster presentation at the conference to solicit feedback. Consequently, specific findings regarding how different speed combinations affect TCC or NASA-TLX scores are not included. The significance of this work lies in its rigorous experimental framework for quantifying the human factors associated with mixed-traffic environments, providing a basis for understanding how speed discrepancies between autonomous and manual vehicles impact driver safety and psychological stress.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | cached | — | — | 3 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| enrich | failed | — | — | — | 2 | 2026-08-23 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 10 | 2026-08-11 |
| verify | partial | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified_with_issues.
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- Empirical Findings: self report data, behavioral performance data
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