Many threat assessment algorithms are based on a collection of threshold equations that predict when a collision is to occur. The fact that there are numerous algorithms suggests a need to understand the underlying principles behind the equation design and threshold settings. In this paper, we present a methodology to develop appropriate alerting thresholds based on performance metrics. This also allows us to compare different alerting algorithms. The method is a performance-based approach in state-space. and can thus be utilized in conjunction with any chosen alerting algorithm or sensor system. Using carefully prescribed trajectory models (which may include uncertainties), the performance tradeoff with and without an alert can be predicted for different states along the course of an encounter situation. This information can then be used to set appropriate threshold values for the desired alerting logic. The development of the threshold criteria for a rear-end collision warning system is given as an example. Though the approach given is presented as a threshold design tool, the methodology is self-contained as a threat assessment logic. The possibility exists to compute the performance measures on-the-fly from which alerting decisions can be made directly.
|Original language||English (US)|
|Title of host publication||IEEE Intelligent Vehicles Symposium, Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Jan 1 2003|