
doi: 10.1109/mis.2005.31
Automobile industry and academic researchers expend considerable effort to develop driver assistance systems. DASs are aware of certain driving situations and support drivers through information, warnings, or even intervention. Many DAS applications are safety oriented, such as lane departure warning systems. Some are comfort oriented, such as automated parking assistants. Moreover, DAS human-machine interfaces must support careful communication with potentially taxed drivers. Driver models support DAS design in several ways. Our work focuses on modeling the tactical level of driving decisions, such as when to brake and whether to accelerate and pass another vehicle. Such decisions are based on local, instantaneously available environmental information about the road and other cars in the same or an adjacent lane.
| 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). | 20 | |
| 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. | Average |
