Things have improved on many fronts since the 2004 challenge. Arguably the biggest difference between the 2004 challenge (best distance was 7 miles) and the 20

Things have improved on many fronts since the 2004 challenge. Arguably the biggest difference between the 2004 challenge (best distance was 7 miles) and the 2005 challenge (5 vehicles finished the race) was simply experience and refinement of existing technology. Stanford and CMU (top finishers) completed the race with very different approaches. The Velodyne lidar was a prototype in the 2005 challenge and the first commercial version was extremely valuable to the teams that used it during the Urban Challenge. Google relied heavily on it and similar sensing technologies while developing their fleet, and many other groups going after full autonomy have also relied on lidar, so it certainly continues to be important. There's lots of different opinions on the future value of lidar vs vision. Camera quality and processing power + the effectiveness of CNNs are pushing a lot of people towards vision as a primary sensor. There's also been a lot of progress for driving in urban environments in modeling, mapping, and prediction. A lot of this comes from collecting lots of data and building maps and behavioral models for objects the vehicle will interact with (cars, people...) Obviously for that the advancements in ML and deep learning don't hurt.