- '18 Degree Show Team
- '16 Atkins - Human Factors
- '17 Diploma in Professional Studies
Final Year Project
The application of autonomous vehicles in the prevention of fatal collisions with motorcycles
Research suggests that over 90% of all crashes are caused or contributed to by human error. It is proposed that autonomous vehicles have the potential to significantly mitigate this by eliminating mistakes routinely made by human drivers. This project investigates the potential effectiveness of camera and sensor configuration in autonomous vehicles in preventing or mitigating the severity of motorcycle collisions.
In the UK, on average, there are 6 deaths and 94 serious injuries every week for motorcycle riders. The development of self-driving technology is anticipated to reduce the frequency of fatal collisions by removing the human error element.
The interaction between cars and other roads users is possible due to humans’ ability to interpret scenarios and make the correct decision based on a range of cues. Additional interactions, including hand gestures, horns and sirens are all additional forms of communication that assist with safe navigation, but are inherently absent in autonomous vehicles.
This project focussed on the effectiveness of the cameras, sensors and radars of three autonomous vehicles, in four collision case studies obtained from police investigation reports. The analysis involved hypothetically substituting the car involved with each autonomous vehicle and following a set of key questions designed to determine whether the vehicle’s sensors and capabilities would have enabled it to mitigate or prevent the collision.
The analysis focused on identifying and comparing vehicle capabilities with the crash environment, enabling conclusions to be drawn.
A Bow-Tie analysis was formulated for each vehicle in each crash scenario with a subsequent amalgamation to identify common causal factors across the accidents and also to highlight gaps where factors are perhaps not mitigated as effectively as they could be.
This project emphasised the number of unanswered questions surrounding the implementation of autonomous vehicles onto the UK’s roads.