
doi: 10.1109/mc.2006.446
We perform an enormous number of functions while driving, and a computer trying to match a human driver must face all of them. Cornell University researchers offer an insider's perspective on the issues the DARPA Grand Challenge competitors faced in creating a humanlike driver - without the human. In preparing for the Grand Challenge, Cornell University's team divided the driving problem into three basic tasks: (i) localization - knowing where you are, (ii) sensing - seeing what's around you, and (iii) path planning etermining how to get to a destination. Creating a vehicle capable of driving itself therefore required finding computational solutions to each of these three tasks
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
