mlsanityData to 7 Oct 2026

Rationale-aware Autonomous Driving Policy utilizing Safety Force Field implemented on CARLA Simulator

arXiv 2211.10237 ↗First posted 18 Nov 2022cs.RO cs.AI cs.LGcited by 1

On the map: End-to-end autonomous driving → Adversarial scenarios and safety testing

Abstract (arXiv)

Despite the rapid improvement of autonomous driving technology in recent years, automotive manufacturers must resolve liability issues to commercialize autonomous passenger car of SAE J3016 Level 3 or higher. To cope with the product liability law, manufacturers develop autonomous driving systems in compliance with international standards for safety such as ISO 26262 and ISO 21448. Concerning the safety of the intended functionality (SOTIF) requirement in ISO 26262, the driving policy recommends providing an explicit rational basis for maneuver decisions. In this case, mathematical models such as Safety Force Field (SFF) and Responsibility-Sensitive Safety (RSS) which have interpretability on decision, may be suitable. In this work, we implement SFF from scratch to substitute the undisclosed NVIDIA's source code and integrate it with CARLA open-source simulator. Using SFF and CARLA, we present a predictor for claimed sets of vehicles, and based on the predictor, propose an integrated driving policy that consistently operates regardless of safety conditions it encounters while passing through dynamic traffic. The policy does not have a separate plan for each condition, but using safety potential, it aims human-like driving blended in with traffic flow.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Adversarial scenarios and safety testing, one of 9 directions in End-to-end autonomous driving. Builds on 17 of its 41 references that are in the map. First posted on arXiv 18 Nov 2022.

Builds on

17 of 41 references.

References · 17

  1. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  2. 2017On a Formal Model of Safe and Scalable Self-driving Carscited by 129
  3. 2021A Survey of Deep RL and IL for Autonomous Driving Policy Learningcited by 59
  4. 2019Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehiclescited by 51
  5. 2019Adaptive Stress Testing with Reward Augmentation for Autonomous Vehicle Validationcited by 33
  6. 2018Probabilistic Prediction of Vehicle Semantic Intention and Motioncited by 31
  7. 2018Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Componentscited by 28
  8. 2019Autonomous Highway Driving using Deep Reinforcement Learningcited by 22
  9. 2019Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Drivingcited by 21
  10. 2020Self-Driving like a Human driver instead of a Robocar: Personalized comfortable driving experience for autonomous vehiclescited by 20
  11. 2019Requirements-driven Test Generation for Autonomous Vehicles with Machine Learning Componentscited by 17
  12. 2020Towards Learning Multi-agent Negotiations via Self-Playcited by 17
5 more
  1. 2019Predicting Vehicle Behaviors Over An Extended Horizon Using Behavior Interaction Networkcited by 15
  2. 2020Fundamental Considerations around Scenario-Based Testing for Automated Drivingcited by 15
  3. 2020Deep Reinforcement Learning for Human-Like Driving Policies in Collision Avoidance Tasks of Self-Driving Carscited by 7
  4. 2019Towards Provably Not-at-Fault Control of Autonomous Robots in Arbitrary Dynamic Environmentscited by 4
  5. 2020Online Verification Concept for Autonomous Vehicles -- Illustrative Study for a Trajectory Planning Modulecited by 3

Built on by

Cited by year

Citing papers per year: 2024: 1.

1 paper.

  1. 2024A Review of Reward Functions for Reinforcement Learning in the context of Autonomous Drivingcited by 17

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  1. 2026A Risk-Field Enhanced Closed-Loop Digital Twin Framework for Autonomous Driving Safety Validation
  2. 2021Runtime Safety Assurance for Learning-enabled Control of Autonomous Driving Vehicles
  3. 2025Towards Benchmarking and Assessing the Safety and Robustness of Autonomous Driving on Safety-critical Scenarios
  4. 2024SafeDrive: Knowledge- and Data-Driven Risk-Sensitive Decision-Making for Autonomous Vehicles with Large Language Models
  5. 2024Enhanced Safety in Autonomous Driving: Integrating Latent State Diffusion Model for End-to-End Navigation
  6. 2021Towards Safe, Explainable, and Regulated Autonomous Driving
  7. 2023A Counterfactual Safety Margin Perspective on the Scoring of Autonomous Vehicles' Riskiness
  8. 2026Safe2Drive: Evaluating Safe Driving Behaviors of E2E Autonomous Driving Models