AV-Occupant Perceived Risk Model for Cut-In Scenarios with Empirical Evaluation (2403.15171v1)
Abstract: Advancements in autonomous vehicle (AV) technologies necessitate precise estimation of perceived risk to enhance user comfort, acceptance and trust. This paper introduces a novel AV-Occupant Risk (AVOR) model designed for perceived risk estimation during AV cut-in scenarios. An empirical study is conducted with 18 participants with realistic cut-in scenarios. Two factors were investigated: scenario risk and scene population. 76% of subjective risk responses indicate an increase in perceived risk at cut-in initiation. The existing perceived risk model did not capture this critical phenomenon. Our AVOR model demonstrated a significant improvement in estimating perceived risk during the early stages of cut-ins, especially for the high-risk scenario, enhancing modelling accuracy by up to 54%. The concept of the AVOR model can quantify perceived risk in other diverse driving contexts characterized by dynamic uncertainties, enhancing the reliability and human-centred focus of AV systems.
- Lane change/merge crashes: Problem size assessment and statistical description. U.S. Department of Transportation National Highway Traffic Safety Administration, 12, 1994.
- Challenges in autonomous vehicle testing and validation. Safety of the Intended Functionality, pages 125–142, 2020.
- ISO 2631. Mechanical vibration and shock – evaluation of human exposure to whole-body vibration, standard. International Organization for Standardization, Geneva, CH, 2001.
- What’s the risk? a comparison of actual and perceived driving risk. Transportation Research Part F: Traffic Psychology and Behaviour, 25:50–64, 2014.
- Standards for passenger comfort in automated vehicles: Acceleration and jerk. Applied Ergonomics, 106, 09 2022.
- Predicting perceived risk of traffic scenes using computer vision. Transportation Research Part F: Traffic Psychology and Behaviour, 93:235–247, 2023.
- Enrico del Re and Cristina Olaverri-Monreal. Implementation of road safety perception in autonomous vehicles in a lane change scenario. In 2022 IEEE International Conference on Vehicular Electronics and Safety (ICVES), pages 1–6, 2022.
- ERTRAC Working Group. Connected automated driving roadmap. Connectivity and Automated Driving, 2019.
- Can driving condition prompt systems improve passenger comfort of intelligent vehicles? a driving simulator study. Transportation Research Part F: Traffic Psychology and Behaviour, 81:240–250, 2021.
- Modelling perceived risk and trust in driving automation reacting to merging and braking vehicles. Transportation Research Part F: Traffic Psychology and Behaviour, 86:178–195, 2022.
- Individual motion perception parameters and motion sickness frequency sensitivity in fore-aft motion. Experimental Brain Research, 6:1727–1745, 9 2021.
- ISO. 26262: 2018: Road vehicles—functional safety. British Standards Institute, 12, 2018.
- Testing autonomous vehicle software in the virtual prototyping environment. IEEE Embedded Systems Letters, 9(1):5–8, 2017.
- Human-like driving behaviour emerges from a risk-based driver model. Nature Communications, 11, 2020.
- A risk field-based metric correlates with driver’s perceived risk in manual and automated driving: A test-track study. Transportation Research Part C: Emerging Technologies, 133:103428, 2021.
- Identification of visual cues and quantification of drivers’ perception of proximity risk to the lead vehicle in car-following situations. Journal of Mechanical Systems for Transportation and Logistics, 1:170–180, 04 2008.
- Threat assessment techniques in intelligent vehicles: A comparative survey. IEEE Intelligent Transportation Systems Magazine, 13(4):71–91, 2021.
- Enhancing passenger comfort in autonomous vehicles through vehicle handling analysis and optimization. IEEE Intelligent Transportation Systems Magazine, 13(3):156–173, 2021.
- Perceived safety and attributed value as predictors of the intention to use autonomous vehicles: A national study with spanish drivers. Safety Science, 120:865–876, 2019.
- Road user hazard perception tests: A systematic review of current methodologies. Accident Analysis & Prevention, 129:309–333, 2019.
- Probabilistic field approach for motorway driving risk assessment. Transportation Research Part C: Emerging Technologies, 118:102716, 2020.
- Evaluating perceived safety of autonomous vehicle: The influence of privacy and cybersecurity to cognitive and emotional safety. IATSS Research, 47(2):160–170, 2023.
- Rcms: Risk-aware crash mitigation system for autonomous vehicles. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023.
- What drives people to accept automated vehicles? findings from a field experiment. Transportation Research Part C: Emerging Technologies, 95:320–334, 2018.