Algorithm to Improve the Predictability for Auto-vehicles' Behaviors and Avoid Risk Accumulation during Driving

We observed that predictable driving behaviors can lead to a reduction of reaction time and safety improvement for auto-driving. In this study, we investigate the different safety alerts related to auto-driving. We design a pre-warning scheme to improve the predictability of driving behaviors for each autonomous vehicle. Based on the pre-warning scheme, we propose an algorithm to predict the safety status for each peer vehicle and extend the concept to a cluster of autonomous vehicles by proposing another algorithm to avoid risk accumulation during driving. We evaluate the effectiveness of proposed algorithms by using various simulations and case illustrations. The simulations showed that the results are promising.