# Bayesian-Based Traffic Safety Evaluation Study for Driverless Infiltration
## 2 Materials and Methods
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Serial** & **Corporations** & **Times** & **Cause of the Accident** & **Accident Results** \\ \hline
1 & Tesla (company) & 16 January & At the time of the accident, the Tesla involved showed no signs of braking or slowing down, nor did it take any evasive action. & A Tesla car crashed directly into a road sweeper in operation, destroying the Tesla car on the spot and killing the driver, Gao \\  & Tesla (company) & 16 January & The Tesla involved showed no signs of braking or slowing down, nor did it take any evasive action. & Yaning. Investigation results showed that the vehicle was traveling at a constant speed at the time of the accident, and Gao Yaning had turned on the driverless function. & Google’s driverless test vehicle was involved in a serious traffic accident in Mountain View, USA, which resulted in serious damage to the driverless test vehicle, which had to leave the scene with the help of a tow truck, but fortunately, the accident did not result in casualties. \\ \hline
3 & Uber & 17 March & At an intersection, a self-driving Uber car traveling north to south collided with a regular vehicle traveling east to west trying to turn left. & An Uber self-driving test vehicle was involved in a crash in Tempe, Arizona. The Uber self-driving car rolled over and another vehicle was severely damaged; fortunately, there were no injuries. \\ \hline
4 & GE & 17 December & The vehicle scraped a motorbike in the process of changing lanes. & A Cruise self-driving car was traveling in autopilot mode on Oak Street, crossing the intersection of Oak and Fillmore Streets before remaining in the third lane heading east. The accident later resulted in a shoulder injury to the motorcyclist. \\ \hline
5 & Argo & 18 January & Ford-funded Argo AI was involved in a traffic accident in Pittsburgh, Pennsylvania, USA. & The accident ended up injuring two people. \\ \hline
6 & Uber & 18 March & A woman in the US state of Arizona has died after being hit by an Uber self-driving vehicle. & The world’s first accident in which a self-driving vehicle killed a pedestrian. \\ \hline
7 & Tesla (company) & 18 January & A Tesla Model S crashed into a parked fire truck. & No injuries were reported on the 405 Freeway in Los Angeles. \\ \hline
8 & Meituan (Japanese company) & 21 October & “Magic Bag 20” and a private car collided at the junction. & In the Shunyi district, damage was caused to the vehicle. \\ \hline
9 & Meituan (Japanese company) & & Meituan’s driverless delivery vehicle was involved in a rear-end collision with a bus on an open road in Beijing’s Shunyi district. & Apart from the direct collision between the sensor in the front of the Magic Bag 20 and the rear of the bus, which may be at risk of damage, there was no obvious damage to either side of the accident and no injuries were caused. \\ \hline
24 & Ngari (preference in Tibet, Tibetan: Mnga’ ris & 22 March & Ali’s “Little Donkey” driverless vehicle drove into a piece of under concrete that had not been landfilled for a long time at Henan University. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Selected textual data. was inferred, the causal relationship was analyzed, and the causal factors present in the accident cases were mined, and finally, 18 driverless accident causal factors were identified. Considering the influence of the key aspects of perception [16; 17; 18; 19], decision [20; 21; 22], and control [23; 24] on driving safety, the 18 causal factors were divided into 5 categories, such as perception risk factor, decision risk factor, control risk factor, road risk factor, and other risk factors, in which P1-P3 are the perception risk factors, D1-D4 are the decision risk factors, C1-C4 are the control risk factors, R1-R4 are the road risk factors and E1-E3 are other risk factors.