# Bayesian-Based Traffic Safety Evaluation Study for Driverless Infiltration
## 5 Summary and Prospect  
### Research Results and Conclusions  
This article conducted statistical analyses through accident cases and expert questionnaires, and the weight of each expert's scoring was calculated for validation to ensure the validity of the data. For the first time, the evaluation system of driverless highway traffic safety risk indicators was established, and the driverless traffic risk assessment model fused with Leaky Noisy-OR-Gate and Bayesian network was innovatively constructed, and the simulation inference analysis was carried out by using the GeNIe visualization tool, which effectively predicted the probability of the occurrence of the target node, and comprehensively evaluated the traffic safety risk under the penetration of driverless driving. By analyzing the driverless risk, it was obtained that the overall risk was in a controllable state, which coincided with the actual traffic risk. The key factors with high sensitivity were further identified. Specifically, they included the long-tail problem of sensors, cameras, and sensing technology in perception risk, the GPS positioning, navigation maps, dynamic planning, and AI learning decision-making software problem in decision-making risk, the emergency braking problem in control risk, and the visibility problem in road risk. Meanwhile, three suggestions were put forward for scientific research institutions in the field of autonomous driving. The three suggestions are hardware and software suppliers, and vehicle companies.  
Policymakers should improve the policies and regulations of the internet of vehicles industry based on the research results and promote cross-industry integration of the internet of vehicles industry. According to the safety evaluation index system in this article, investment in unmanned vehicle manufacturing enterprises, single-point technology solutions, overall solutions, sensors, artificial intelligence software, and hardware should be increased, and policy support should be provided. The regulatory authorities focus on managing the key units of perception, decision-making, and risk control, requiring autonomous driving production enterprises to actively control the source, strengthen industry self-discipline, actively participate in policy formulation and implementation processes, and ensure effective management and safe operation supervision of autonomous driving. With the improvement of autonomous driving policies and regulations, the effective management of regulatory authorities, and the supervision of safe operation, several major technology giants have begun to lay out autonomous vehicles. Unmanned new energy-sharing vehicles are about to enter commercial pilot operation, which will have a profound impact on the broader transportation industry.  
In the coming period, efforts should be made to break through the bottleneck of perception, decision-making, and control technology of driverless vehicles, with a view to reasonably and effectively controlling the traffic safety risks under the penetration of driverless vehicles in a targeted manner, avoiding the escalation of the degree of risk or the expansion of the risk loss. This should be done by formulating the corresponding control measures and improving the level of safety preventive and control measures, providing a new idea for the management of driverless traffic safety risks, and providing a theoretical basis for the risk control measures to be the formulation and implementation of the theoretical basis. It is believed that in the near future, driverless vehicles will fundamentally change the human traveling mode, which will largely improve traveling safety and open up new solutions for reducing traffic congestion.