A case study of unavoidable accidents of autonomous vehicles

Abstract

Objective: Autonomous driving technology eliminates human errors, and thus it is a promising solution for reducing road traffic fatalities and injuries. While future autonomous driving technology may be able to reduce the number of collision accidents, it will not be able to avoid all collision accidents. This study is aimed to demonstrate why some accidents will still be unavoidable even with advanced perceiving and controlling capabilities.

Methods: Because fully autonomous vehicles are currently in the laboratory stage, we used the prospective method to study the unavoidable accident of autonomous vehicles. Suitable traffic accident cases were screened from the China In-Depth Accident Study (CIDAS). Videos of the accidents were analyzed and the accidents were reconstructed using PC-Crash software. We assumed that target vehicle possesses near-perfect autonomous driving capabilities. Unavoidable accidents were determined based on vehicle dynamics and traffic constraints. The time from perceiving hazard to collision was calculated for each accident.

Results: Among the 112 accidents screened, 15 cases of unavoidable accidents were identified. Three typical cases are presented in detail in this study. Based on the reasons why the target vehicles cannot avoid the collisions, we classified the unavoidable accidents into time-limit type and space-limit type. Time-limit means that vehicle cannot stop or steer out of danger in time, and space-limit means that the traffic environment does not have sufficient space for vehicle to avoid collision.

Conclusions: Collision accidents will still occur even with perfect autonomous driving technology. We used the prospective method to investigate scenarios and characteristics of unavoidable accidents of autonomous vehicles. The time-limit type and the space-limit type were identified as two categories of unavoidable accidents. For the time-limit unavoidable accidents, the time from perceiving hazard to collision is typically not longer than 1.5s. The characteristics of unavoidable accidents and the estimated pre-crash warning time can provide some reference for establishing future occupant protection strategies. This study also showed the limitations of active safety and the necessity of passive safety.

Keywords:

• Autonomous vehicles
• accident analysis
• unavoidable accidents
• occupant protection

Acknowledgments

The authors would like to thank Mr. Xudong Li and Mr. Peng Wang for their contributions to the data collection of traffic accidents in the field and database administration as well as the initial data screening for this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This study was supported by the National Key R&D Program of China (2017YFE0118400).