Preferred Following Distance as a Function of Speed—Function-Specific Automation (Level 1) Applications
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Summary
This study investigates driver comfort and safety preferences regarding following distances in Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) systems. As these Level 1 automation technologies become prevalent, their impact on roadway safety and capacity depends heavily on whether the system’s gap parameters align with driver acceptance. The research aimed to develop time-gap curves describing comfortable and minimally safe following distances across various speeds, comparing these human preferences against the behavior of a commercially available ACC system. The experiment involved 24 participants from the Washington, D.C. metropolitan area who drove a 2012 sedan equipped with ACC. Each participant completed two trips along an experimental route in Virginia: one manual drive and one with ACC engaged at its closest setting. The route included nine test segments with speeds ranging from 25 to 65 mi/h. During the ACC trial, participants rated their comfort with the system’s following distance on a 1–5 scale at approximately one-minute intervals. During the manual trial, researchers recorded the participants’ naturally comfortable following distances and prompted them to identify their minimally safe following distances. Data were collected via car area network (CAN) and GPS systems, with analysis focusing on time gaps binned by actual vehicle speed. Results indicated that the tested ACC system utilized a hybrid approach: it maintained a fixed distance of approximately 24 meters at speeds below 40 mi/h, switching to a stable time gap of roughly 1.4 seconds at higher speeds. Most participants rated the ACC gap as comfortable across all speeds, though some found it too far at 45 mi/h and too close at other instances. In manual driving, the difference between comfortable and minimally safe time gaps remained stable at approximately 0.35–0.39 seconds across all speeds. Comparing the two modes, ACC gaps were generally similar to manual driving preferences. However, ACC was more conservative (larger gap) at low speeds (25–30 mi/h) and slightly closer than manual drivers at 40–45 mi/h. At the highest speed (65 mi/h), manual drivers selected larger time gaps than the ACC system. The findings provide empirical guidelines for ACC and CACC developers to align system parameters with driver comfort, which is critical for technology adoption and safety. By identifying that drivers prefer variable time gaps that adjust with speed, the study suggests that ACC systems should avoid fixed-distance logic at low speeds and ensure time gaps at high speeds do not fall below driver comfort thresholds. These insights help optimize the balance between operational efficiency, such as increased roadway capacity, and user acceptance, ensuring that automated systems support rather than hinder safe driving behaviors.
Key finding
ACC gap distances were generally similar to manual comfortable gaps, though the system used a fixed distance gap below 40 mi/h and a stable time gap above that speed.
Methodology
on_road
Sample size: 24
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