Towards Standardization of AV Safety: C++ Library for Responsibility Sensitive Safety

Gaßmann, Bernd; Oboril, Fabian; Buerkle, Cornelius; Liu, Shuang; Yan, Shoumeng; Elli, Maria Soledad; Álvarez, Ignacio; Aerrabotu, Naveen; Jaber, Suhel; Beek, Peter van der; Iyer, Darshan; Weast, Jack

doi:10.1109/ivs.2019.8813885

Cited by 45 publications

(13 citation statements)

References 4 publications

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“…. , M denotes the index of each obstacle and d min is the minimum safe distance from the responsibility-sensitive safety (RSS) model [26], [27]. σ i x and σ i y determine the shape of the obstacle's PF based on the relative speed and distance between the ego-vehicle and the obstacle.…”

Section: B Obstacle Potential Functionmentioning

confidence: 99%

Model Predictive Path-Planning Controller With Potential Function for Emergency Collision Avoidance on Highway Driving

Lin

Tsukada

2022

IEEE Robot. Autom. Lett.

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Existing potential functions (PFs) utilized in autonomous vehicles mainly focus on solving the path-planning problems in some conventional driving scenarios; thus, their performance may not be satisfactory in the context of emergency obstacle avoidance. Therefore, we propose a novel model predictive path-planning controller (MPPC) combined with PFs to handle complex traffic scenarios (e.g., emergency avoidance when a sudden accident occurs). Specifically, to enhance the safety of the PFs, we developed an MPPC to handle an emergency case with a sigmoid-based safe passage embedded in the MPC constraints (SPMPC) with a specific triggering analysis algorithm on monitoring traffic emergencies. The presented PF-SPMPC algorithm was compiled in a comparative simulation study using MATLAB/Simulink and CarSim. The algorithm outperformed the latest PF-MPC approach to eliminate the severe tire oscillations and guarantee autonomous driving safety when handling the traffic emergency avoidance scenario.

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Section: B Obstacle Potential Functionmentioning

confidence: 99%

Model Predictive Path-Planning Controller With Potential Function for Emergency Collision Avoidance on Highway Driving

Lin

Tsukada

2022

IEEE Robot. Autom. Lett.

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“…I. The parameters are similar to the ones that have been validated in other studies considering RSS [53]- [55]. However, we adjust the reaction time to 0.5s as a compromise between reasonable reaction times for humans and AVs [56], [57].…”

Section: A Considered Specification and Datasetmentioning

confidence: 99%

Risk-aware Motion Planning for Autonomous Vehicles with Safety Specifications

Nyberg

Pek

Col

et al. 2021

2021 IEEE Intelligent Vehicles Symposium (IV)

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“…The maximum acceleration and minimum deceleration values are assumed to be the same because they are determined by the following vehicle with autonomous driving function. Moreover, the maximum deceleration of the leading vehicle and the response time of the autonomous vehicle were cited [39]. Equations ( 3)-( 5) represent the derived RSS safety distance calculation formulas of the 2.5 T gasoline, 3.5 T gasoline, and 3.0 diesel models, respectively.…”

Section: Derive Rss Models and Identify Safe Distances By Speedmentioning

confidence: 99%

On the Development of Autonomous Vehicle Safety Distance by an RSS Model Based on a Variable Focus Function Camera

Kim

Yu²,

Kim³

et al. 2021

Sensors

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Today, a lot of research on autonomous driving technology is being conducted, and various vehicles with autonomous driving functions, such as ACC (adaptive cruise control) are being released. The autonomous vehicle recognizes obstacles ahead by the fusion of data from various sensors, such as lidar and radar sensors, including camera sensors. As the number of vehicles equipped with such autonomous driving functions increases, securing safety and reliability is a big issue. Recently, Mobileye proposed the RSS (responsibility-sensitive safety) model, which is a white box mathematical model, to secure the safety of autonomous vehicles and clarify responsibility in the case of an accident. In this paper, a method of applying the RSS model to a variable focus function camera that can cover the recognition range of a lidar sensor and a radar sensor with a single camera sensor is considered. The variables of the RSS model suitable for the variable focus function camera were defined, the variable values were determined, and the safe distances for each velocity were derived by applying the determined variable values. In addition, as a result of considering the time required to obtain the data, and the time required to change the focal length of the camera, it was confirmed that the response time obtained using the derived safe distance was a valid result.

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Towards Standardization of AV Safety: C++ Library for Responsibility Sensitive Safety

Cited by 45 publications

References 4 publications

Model Predictive Path-Planning Controller With Potential Function for Emergency Collision Avoidance on Highway Driving

Model Predictive Path-Planning Controller With Potential Function for Emergency Collision Avoidance on Highway Driving

Risk-aware Motion Planning for Autonomous Vehicles with Safety Specifications

On the Development of Autonomous Vehicle Safety Distance by an RSS Model Based on a Variable Focus Function Camera

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