Autonomous vehicles have made remarkable progress over the past decade. Driverless cars and buses that once struggled to stay in lane can now navigate busy city streets, recognise pedestrians and cyclists, and respond smoothly to traffic signals.
Yet one challenge remains stubbornly difficult. The hardest situations on the road are not the common ones but the rare and unpredictable events – what AI researchers call “long-tail scenarios” or “edge cases”, because they occur as outliers on any event distribution curve.
Examples include unexpected roadworks, unusual behaviour from other road users, and other subtle situations where there is a very low probability of something happening – but which would have a significant impact on the vehicle and journey.
