Risk Measurement, Risk Entropy, and Autonomous Driving Risk Modeling
This addresses risk management challenges in autonomous driving for insurers and developers, though it appears incremental by adapting existing risk modeling concepts to this new domain.
The paper tackles risk modeling for autonomous driving by developing a novel model that better aligns with real traffic and safety performance, providing technical feasibility for risk assessment and insurance pricing in simulation environments.
It has been for a long time to use big data of autonomous vehicles for perception, prediction, planning, and control of driving. Naturally, it is increasingly questioned why not using this big data for risk management and actuarial modeling. This article examines the emerging technical difficulties, new ideas, and methods of risk modeling under autonomous driving scenarios. Compared with the traditional risk model, the novel model is more consistent with the real road traffic and driving safety performance. More importantly, it provides technical feasibility for realizing risk assessment and car insurance pricing under a computer simulation environment.