Design Consistency on Corridors

Cunningham, Christopher M.; Chase, R. Thomas; Yang, Guangchuan; Wright, Waugh; Pyo, Kihyun; Kaber, David; Liu, Yunmei · 2022 · ROSA P / North Carolina. Department of Transportation. Research and Analysis Group

archive: archived pipeline: cataloged verified

Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)

Summary

This study addresses the lack of guidance regarding the corridor-level deployment of Alternative Intersection and Interchange (AII) designs, specifically focusing on driver confusion when adjacent intersections utilize different unconventional maneuvers. While AIIs like Median U-turns (MUT), Restricted Crossing U-turns (RCUT), and Quadrant Roadway Intersections (QRI) offer operational and safety benefits, their varying geometric and control features create challenges for drivers navigating corridors with mixed designs. The research aimed to identify viable combinations of adjacent AII designs, assess driver understanding, and evaluate driver performance in terms of navigation and vehicle control. The methodology combined a state-of-the-practice literature review, focus group interviews, and a controlled driving simulator experiment. The literature review identified four primary AII types (RCI, MUT, CFI, QRI) alongside conventional intersections. Focus groups gathered qualitative data on driver familiarity and confusion, revealing that while experienced drivers could often guess correct lanes, they struggled with memorizing specific configurations, and all participants recommended earlier and more prominent signage. The core experimental component involved 48 participants navigating nine simulator scenarios featuring 12 distinct intersection pairs. These pairs tested the impact of a "preceding intersection" on performance at a "test intersection," measuring failed movements (FMs), approach speeds, hard braking events, and lane changes. Key findings from the simulator data indicated that overall failed movements were similar across standard, RCI-dominant, and mixed AII corridors. However, the configuration of adjacent intersections significantly impacted performance. Failed movements increased when the preceding intersection was an RCUT, with the combination of an RCUT preceding a MUT resulting in the highest failure rates. Specifically, minor left turns at MUT intersections and side-through movements at RCIs generated the most failures, whereas QRI and conventional main left turns had the fewest. Conversely, an RCUT preceding a QRI test intersection proved to be the easiest combination for drivers. Hard braking events were less frequent in MUT and RCUT corridors lacking predominantly traditional intersections. Additionally, driver performance improved significantly with repeated trials, with over half of all failures occurring during the first trial, suggesting that familiarity mitigates confusion. Drivers cited unclear signs, missed signage, and geometric confusion as primary causes for errors. The study concludes that while mixed AII corridors do not inherently degrade overall driver performance compared to traditional corridors, specific adjacent combinations create significant cognitive loads. The RCUT-to-MUT transition is particularly challenging, while RCUT-to-QRI transitions are manageable. The findings imply that NCDOT and other agencies should consider design consistency or enhanced advance signing when deploying mixed AII corridors. The results highlight that driver confusion is largely driven by unfamiliarity and insufficient advance warning, suggesting that improved signage and adequate spacing between unique intersection types are critical for safe navigation.

Key finding

The combination of a Reduced Conflict Intersection (RCI) preceding a Median U-turn (MUT) intersection resulted in the highest number of driver failed movements, indicating it is the most challenging corridor configuration for navigation.

Methodology

simulator

Sample size: 48

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).

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

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• intersection design
• perceptual countermeasures
• rail grade crossings
• roadway lighting effects
• work zones
• signaling behavior

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: behavioral performance data
• Methodological Resource: dataset resource