Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning
Autonomous vehicles are being developed to make road traffic safer in the future. The time when autonomous vehicles are actually safe enough to be used in real traffic is a current subject of discussion between industry, science, and society. In our work, we propose a new approach to the risk assess...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10195149/ |
| _version_ | 1797743395514351616 |
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| author | Maximilian Geisslinger Rainer Trauth Gemb Kaljavesi Markus Lienkamp |
| author_facet | Maximilian Geisslinger Rainer Trauth Gemb Kaljavesi Markus Lienkamp |
| author_sort | Maximilian Geisslinger |
| collection | DOAJ |
| description | Autonomous vehicles are being developed to make road traffic safer in the future. The time when autonomous vehicles are actually safe enough to be used in real traffic is a current subject of discussion between industry, science, and society. In our work, we propose a new approach to the risk assessment of autonomous vehicles based on risk-benefit analysis, as it is already established in other areas, such as the registration of pharmaceuticals. In this context, we address the question of socially acceptable risk for mobility and investigate this concept as a decision-making criterion in trajectory planning. We make the first attempt to quantify an accepted risk by comparing autonomous vehicles with other types of mobility while taking into account the ethical and psychological effects important to the acceptance of autonomous vehicles. We show how an accepted risk contributes to the transparent decision-making of autonomous vehicles at the maneuver level. Finally, we present a method for considering accepted risk in trajectory planning. The evaluation of this algorithm in a simulation of 2,000 scenarios reveals that lower risk thresholds can actually reduce risks in trajectory planning. The code used in this research is publicly available as open-source software: <uri>https://github.com/TUMFTM/EthicalTrajectoryPlanning</uri>. |
| first_indexed | 2024-03-12T14:55:51Z |
| format | Article |
| id | doaj.art-a990fb9404a24d4d9faa1b7baccd471e |
| institution | Directory Open Access Journal |
| issn | 2687-7813 |
| language | English |
| last_indexed | 2024-03-12T14:55:51Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj.art-a990fb9404a24d4d9faa1b7baccd471e2023-08-14T23:00:58ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132023-01-01457057910.1109/OJITS.2023.329897310195149Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory PlanningMaximilian Geisslinger0https://orcid.org/0000-0002-6079-1348Rainer Trauth1https://orcid.org/0000-0002-3801-6855Gemb Kaljavesi2https://orcid.org/0009-0008-6311-4554Markus Lienkamp3Institute of Automotive Technology, Technical University of Munich, Garching, GermanyInstitute of Automotive Technology, Technical University of Munich, Garching, GermanyInstitute of Automotive Technology, Technical University of Munich, Garching, GermanyInstitute of Automotive Technology, Technical University of Munich, Garching, GermanyAutonomous vehicles are being developed to make road traffic safer in the future. The time when autonomous vehicles are actually safe enough to be used in real traffic is a current subject of discussion between industry, science, and society. In our work, we propose a new approach to the risk assessment of autonomous vehicles based on risk-benefit analysis, as it is already established in other areas, such as the registration of pharmaceuticals. In this context, we address the question of socially acceptable risk for mobility and investigate this concept as a decision-making criterion in trajectory planning. We make the first attempt to quantify an accepted risk by comparing autonomous vehicles with other types of mobility while taking into account the ethical and psychological effects important to the acceptance of autonomous vehicles. We show how an accepted risk contributes to the transparent decision-making of autonomous vehicles at the maneuver level. Finally, we present a method for considering accepted risk in trajectory planning. The evaluation of this algorithm in a simulation of 2,000 scenarios reveals that lower risk thresholds can actually reduce risks in trajectory planning. The code used in this research is publicly available as open-source software: <uri>https://github.com/TUMFTM/EthicalTrajectoryPlanning</uri>.https://ieeexplore.ieee.org/document/10195149/autonomous vehiclestrajectory planningdecision-makingrisk |
| spellingShingle | Maximilian Geisslinger Rainer Trauth Gemb Kaljavesi Markus Lienkamp Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning IEEE Open Journal of Intelligent Transportation Systems autonomous vehicles trajectory planning decision-making risk |
| title | Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning |
| title_full | Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning |
| title_fullStr | Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning |
| title_full_unstemmed | Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning |
| title_short | Maximum Acceptable Risk as Criterion for Decision-Making in Autonomous Vehicle Trajectory Planning |
| title_sort | maximum acceptable risk as criterion for decision making in autonomous vehicle trajectory planning |
| topic | autonomous vehicles trajectory planning decision-making risk |
| url | https://ieeexplore.ieee.org/document/10195149/ |
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