Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy
DOI: 10.1109/ojits.2024.3397959
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Summary
This paper addresses the safety challenges of autonomous vehicles (AVs) operating in mixed traffic flows alongside human-driven vehicles (HDVs). While Responsibility-Sensitive Safety (RSS) provides a formal framework for AV safety, it assumes all vehicles adhere to safety rules. In mixed traffic, HDVs may violate these rules, creating a "dilemma" where an AV is forced to choose between colliding with its leader or its follower. The authors generalize this concept to "polylemma," a scenario in platoons where a single HDV violation inevitably causes at least one crash among neighboring vehicles. To mitigate this, the study proposes a Human-Error-Tolerant (HET) driving strategy, wherein AVs maintain additional gaps and prepare for moderate deceleration to accommodate potential human errors. The methodology involves defining the dilemma and trilemma scenarios mathematically and extending them to arbitrary platoon sizes. The authors derive the critical distances and deceleration rates required to avoid these collisions. They then analyze real-world trajectory data to calculate the occurrence probability of polylemma scenarios and evaluate the impact of the HET strategy. Specifically, the study quantifies risk reduction and capacity variations at different market penetration rates (MPR) of AVs, considering how background traffic flow speed influences these outcomes. The results indicate that the HET strategy significantly improves safety in mixed traffic. Analysis of real-world data shows that a 50% market penetration rate of AVs using the HET strategy would reduce risks associated with human error by 80%. However, this safety improvement comes with a trade-off in traffic capacity. The decrease in capacity varies depending on the speed of the background traffic flow, as the additional gaps and moderate decelerations required by the HET strategy reduce the overall density of vehicles that can safely occupy the road. The significance of this work lies in its practical approach to AV safety in realistic, mixed-traffic environments. By acknowledging that HDVs cannot be controlled and may behave erratically, the proposed HET strategy offers a viable method for AVs to indirectly reduce collision risks. The findings suggest that even partial adoption of AVs equipped with error-tolerant strategies can yield substantial safety benefits, mitigating the majority of accidents caused by human error. This contributes to the broader field of intelligent transportation systems by providing a quantifiable framework for balancing safety and efficiency in the transition toward autonomous driving.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-20 |
| archive | success | unpaywall | — | — | 2 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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