Traffic simulation tools are an integral element of decision support systems for the evaluation and operation of transportation systems under extreme conditions. However, traffic models do not offer an explicit representation of so-called "panic behavior" that may be encountered under such situations. This type of behavior may result in both qualitative and quantitative differences in the resulting properties and performance of the traffic system. The purpose of this paper is to assess the suitability of existing microscopic traffic models for representing driver behavior under extreme conditions. Several traits and behaviors observed in psychological and sociological studies of panic are mapped onto resulting transportation and driver characteristics. Microscopic traffic models are then evaluated for the extent to which they capture such features of panic behavior of drivers. The main category of microscopic driver behavior situations that is addressed is Acceleration or Car-Following Models. The gaps in the ability of existing models to represent certain aspects of driver behavior under extreme conditions are highlighted. Modifications of existing models to provide better representation of these behaviors are suggested, and an example is presented with a modification of a well-know class of acceleration models.