One in five (22%) fatal and serious collisions could be prevented with the initial introduction of automated vehicles – potentially making them the biggest change in road safety since the introduction of the seatbelt. The TRL analysis suggests the arrival of automated vehicles is likely to bring the biggest change in road safety since the introduction of the seatbelt Research carried out by TRL for a new report using an interim scenario of traditional and autonomous vehicles coexisting revealed that 22% of collisions could be avoided if one of the vehicles was replaced by a level 4 automated vehicle – preventing some 650 fatal and serious injuries annually.
The research – based on between 8%-19% of the total car fleet being autonomous – also suggested there will be reductions in collisions at junctions (10%), collisions involving vulnerable road users (10%) and single vehicle run off road collisions (12%).
The study used a methodology that could be used to investigate the potential effect of the introduction of automated vehicles on the future collision scene. This methodology was applied to a limited scope of collisions; one and two vehicle collisions involving at least one car that resulted in a fatal or serious injury.
However, TRL also said publicly available aggregated data about the introduction of automated technology into the vehicle fleet and its behaviour in near misses and collision scenarios is required to build a better picture of future collisions and opportunities for improving occupant protection.
Richard Cuerden, director of the TRL Academy, commented: “Whilst individual companies are collecting data relating to the performance of their technology in collisions and near misses, what we need is for OEMs and technology providers to come together to help develop an aggregate data set to provide a better picture of uptake of automated vehicles within the vehicle fleet and collision rates of automated vehicles.
“It is also essential to ensure the right high-tech expertise is in place to investigate collisions that involve automated vehicle technologies so that lessons can be learnt as quickly as possible to determine how improvements can be made in the future.”