Cooperative Adaptive Cruise Control Human Factors Study : Experiment 2 : Merging Behavior

Balk, Stacy A.; Jackson, Steven; Philips, Brian H. · 2016 · ROSA P / United States. Federal Highway Administration

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Summary

This study investigates the human factors associated with Cooperative Adaptive Cruise Control (CACC), specifically focusing on driver performance during merging maneuvers into dedicated CACC lanes. The research addresses the challenge of integrating human-driven vehicles into automated platoons, which operate with shorter following gaps to increase roadway capacity. The primary goal was to assess drivers' abilities to successfully enter established CACC platoons and to evaluate the associated workload and physiological arousal. The study assumes a V2V-based system where vehicles act selfishly to maintain personal gaps, requiring merging drivers to adapt to tight spacing without external permission requests. The experiment was conducted using the Federal Highway Administration Highway Driving Simulator with 48 licensed participants divided into three groups: a control group driving manually, a CACC group without merge assistance (manual speed control during merges), and a CACC group with longitudinal speed assistance (automated speed control during merges). Participants performed four merge maneuvers into a continuous stream of traffic with a constant 1.1-second gap. Data collection included the NASA Task Load Index for workload, galvanic skin response (GSR) and eye-tracking metrics for physiological arousal, and collision records for safety performance. Results indicated that CACC significantly reduced perceived driver workload compared to manual driving. Crucially, the CACC system eliminated collisions during merges; participants in both manual conditions experienced collisions in 18% of merge attempts, suggesting that certain gaps were too small for safe manual entry at high speeds. While physiological arousal (measured by GSR) increased during merges across all groups, it did not differ significantly between experimental conditions. Participant feedback suggested that collisions in manual groups often stemmed from expectations of courteous gap creation by other drivers, a behavior unlikely in selfish V2V systems. The findings imply that longitudinal speed assistance is critical for safe merging into CACC platoons with short gaps. The study concludes that while CACC reduces workload and prevents collisions, the lack of gap accommodation in V2V systems poses a significant safety risk for manual merging. These results inform transportation professionals about the necessity of automated assistance for merging and highlight the potential mismatch between driver expectations of courteous traffic behavior and the operational reality of automated platoons.

Key finding

Drivers using CACC with longitudinal merge assistance experienced zero collisions and significantly lower workload compared to drivers who manually controlled speed during merges, who suffered collisions in 18 percent of attempts.

Methodology

simulator

Sample size: 48

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• gap acceptance
• traffic density
• following distance

Information type

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• Empirical Findings: behavioral performance data
• Methodological Resource: tool software
• Theoretical Contribution: computational model