Descriptive and inferential statistics of serious accidents involving considerably automated vehicles-A necessity of smart cities

This article analyses a dataset of past serious accidents involving considerably automated vehicles despite the moderately small size of the dataset due to the currently restrictive legalization of such vehicles globally. Both descriptive and inferential statistics are presented as to the prevalence of accidents as impacted by such situational parameters as the terrain, period of the day, visibility, weather condition, automated vehicle speed, automation system status, accident type and road curvature. The key finding is that the ratio of the accident count with the automation system status being on to that with it being off (i.e. manual driving per se) is substantially smaller at a high speed (74 km per hr or above) of the vehicle than at a low speed.