Assessment of Pedestrian Safety and Driver Behavior Near an Automated Vehicle
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Summary
This study investigates the safety interactions between low-speed automated vehicles (LSAVs) and human-driven vehicles, specifically focusing on driver behavior near the Med City Mover (MCM), an automated shuttle pilot in Rochester, Minnesota. Motivated by anecdotal reports of aggressive overtaking and following behaviors near the MCM, the research aimed to scientifically assess how LSAV presence, speed, and communication strategies influence manual drivers, particularly regarding pedestrian safety risks. The study sought to determine if the MCM’s operational characteristics created unintended hazards, such as increased overtaking or queuing, that could lead to crashes involving pedestrians or other vehicles. The researchers employed a multi-method approach comprising interviews, field observations, and simulation studies. Semi-structured interviews were conducted with LSAV manufacturers and operators to identify common safety challenges. A field study collected data from May 2022 to August 2023 at seven signalized and unsignalized intersections along the MCM route, comparing driver behaviors near the MCM versus human-driven vehicles. Additionally, three simulation studies were conducted: a low-fidelity video study at the Minnesota State Fair (N=85), a crowdsourced survey (N=242) evaluating external human-machine interfaces (eHMIs), and a high-fidelity driving simulation (N=46) testing specific signaling conditions. Results indicated that while the MCM yielded to pedestrians at significantly higher rates than manual vehicles, it also triggered increased risks. Drivers were significantly more likely to overtake the MCM and commit "multiple threat passes" (overtaking while a pedestrian is crossing) compared to human-driven vehicles. The MCM’s exceptionally slow speed (approx. 11 mph) caused larger vehicle queues behind it, which partially mediated the risk of overtaking. Simulation studies revealed that lead vehicle speed was directly correlated with overtaking tendency, with lower speeds increasing aggressive behavior. Furthermore, participants frequently misinterpreted the MCM’s flashing hazard lights as indicating loading/unloading rather than yielding to pedestrians. In contrast, a proposed eHMI using text and icons on an LED screen resulted in participants being nearly twice as likely to wait behind the shuttle and 40% less likely to commit a multiple threat pass compared to the hazard light condition. The findings suggest that while LSAVs can improve pedestrian yielding compliance, their current operational parameters may indirectly increase crash risks through altered driver behavior. The authors recommend increasing LSAV speeds to better match local traffic flow to reduce queuing and overtaking. Crucially, they advise improving eHMIs by restricting hazard light use to emergencies and adopting clear text/icon displays to communicate vehicle intent, such as yielding to pedestrians. These adjustments are expected to enhance driver understanding and reduce unsafe passing behaviors, thereby promoting safer integration of automated shuttles into mixed-traffic environments.
Key finding
Drivers exhibited significantly higher rates of overtaking and multiple-threat passing near the low-speed automated shuttle compared to manual vehicles, a behavior driven by slow speeds, large queues, and misinterpreted hazard signals, which can be mitigated by improved external human-machine interfaces and higher operating speeds.
Methodology
mixed_methods
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.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- ehmi external hmi
- driver vru interaction
- vru facing ehmi
- automation surprise
- pedestrian behavior perception
- rail grade crossings
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, observational prevalence
- Theoretical Contribution: computational model