Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy
The safety of autonomous vehicles (AVs) is a critical consideration for their widespread adoption. Responsibility sensitive safety (RSS) is proposed to serve as a model checking tool for AV safety. However, RSS alone cannot guarantee safety when they are mixed with human-driven vehicles (HDVs). Thes...
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| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
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| Online Access: | https://ieeexplore.ieee.org/document/10525067/ |
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| author | Hongsheng Qi |
| author_facet | Hongsheng Qi |
| author_sort | Hongsheng Qi |
| collection | DOAJ |
| description | The safety of autonomous vehicles (AVs) is a critical consideration for their widespread adoption. Responsibility sensitive safety (RSS) is proposed to serve as a model checking tool for AV safety. However, RSS alone cannot guarantee safety when they are mixed with human-driven vehicles (HDVs). These HDVs may disregard safety rules, creating dilemmas for AVs where they must choose between crashing into their leader or crashing into their follower. This manuscript defines this dilemma regarding the longitudinal driving and extends it to platooning scenarios with an arbitrary number of vehicles, referred to as polylemma. In polylemma, a violation of safety rules by one vehicle inevitably results in at least one crash between neighboring vehicles. To avoid the polylemma scenario, the manuscript proposes a human error-tolerant (HET) driving strategy, wherein AVs maintain an additional gap and prepare for moderate deceleration to account for potential errors by human drivers. The manuscript derives the risk reduction and capacity variation resulting from the implementation of this strategy at a given market penetration rate (MPR) using real world trajectory data. The analysis indicates that a 50% MPR would reduce risks due to human error by 80%, with a decrease in capacity which vary different for background traffic flow speed. |
| format | Article |
| id | doaj-art-0239256a04eb48c3a77f70518ead9ebe |
| institution | Kabale University |
| issn | 2687-7813 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj-art-0239256a04eb48c3a77f70518ead9ebe2025-01-24T00:02:40ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132024-01-01526528010.1109/OJITS.2024.339795910525067Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving StrategyHongsheng Qi0https://orcid.org/0000-0002-2934-7601College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, ChinaThe safety of autonomous vehicles (AVs) is a critical consideration for their widespread adoption. Responsibility sensitive safety (RSS) is proposed to serve as a model checking tool for AV safety. However, RSS alone cannot guarantee safety when they are mixed with human-driven vehicles (HDVs). These HDVs may disregard safety rules, creating dilemmas for AVs where they must choose between crashing into their leader or crashing into their follower. This manuscript defines this dilemma regarding the longitudinal driving and extends it to platooning scenarios with an arbitrary number of vehicles, referred to as polylemma. In polylemma, a violation of safety rules by one vehicle inevitably results in at least one crash between neighboring vehicles. To avoid the polylemma scenario, the manuscript proposes a human error-tolerant (HET) driving strategy, wherein AVs maintain an additional gap and prepare for moderate deceleration to account for potential errors by human drivers. The manuscript derives the risk reduction and capacity variation resulting from the implementation of this strategy at a given market penetration rate (MPR) using real world trajectory data. The analysis indicates that a 50% MPR would reduce risks due to human error by 80%, with a decrease in capacity which vary different for background traffic flow speed.https://ieeexplore.ieee.org/document/10525067/Mixed autonomous vehiclesresponsibility sensitive safetyhuman driver error tolerantpolylemma avoidancelongitudinal driving strategy |
| spellingShingle | Hongsheng Qi Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy IEEE Open Journal of Intelligent Transportation Systems Mixed autonomous vehicles responsibility sensitive safety human driver error tolerant polylemma avoidance longitudinal driving strategy |
| title | Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy |
| title_full | Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy |
| title_fullStr | Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy |
| title_full_unstemmed | Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy |
| title_short | Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy |
| title_sort | dilemma of responsibility sensitive safety in longitudinal mixed autonomous vehicles flow a human driver error tolerant driving strategy |
| topic | Mixed autonomous vehicles responsibility sensitive safety human driver error tolerant polylemma avoidance longitudinal driving strategy |
| url | https://ieeexplore.ieee.org/document/10525067/ |
| work_keys_str_mv | AT hongshengqi dilemmaofresponsibilitysensitivesafetyinlongitudinalmixedautonomousvehiclesflowahumandrivererrortolerantdrivingstrategy |