  Every year, many people are killed and injured in highway traffic accidents.
In order to reduce such casualties, collisions warning systems has been studied
extensively. These systems are built by taking the driver reaction times into
account. However, most of the existing literature focuses on characterizing how
driver reaction times vary across an entire population. Therefore, many of the
warnings that are given turn out to be false alarms. A false alarm occurs
whenever a warning is sent, but it is not needed. This would nagate any safety
benefit of the system, and could even reduce the overall safety if warnings
become a distraction. In this paper, we propose our solution to address the
described problem; First, we briefly describe our method for estimating the
distribution of brake response times for a particular driver using data from a
Vehicular Ad-Hoc Network (VANET) system. Then, we investigate how brake
response times of individual drivers can be used in collision warning
algorithms to reduce false alarm rates while still maintaining a high level of
safety. This will yield a system that is overall more reliable and trustworthy
for drivers, which could lead to wider adoption and applicability for V2V/V2I
communication systems. Moreover, we show how false alarm rate varies with
respect to probability of accident. Our simulation results show that by
individualizing collision warnings the number of false alarms can be reduced
more than $50\%$. Then, we conclude safety applications could potentially take
full advantage of being customized to an individual's characteristics.
