# Simulation-Oriented Analysis and Modeling of
## 7 Discussion and Conclusions  
This study proposes a microscopic traffic flow model (i.e. IDM-distraction) that considers distraction characteristics to simulate distracted driving behavior. Two types of distraction parameters are considered in the model, namely reaction time delay and perception deviation in speed difference and following distance. Compared to existing deterministic models, IDM-distraction uses probability distributions to represent these parameters, capturing the inherent uncertainty and individual differences in distracted driving behavior. By distinguishing road environments and categorizing distracted driving behaviors, behavioral characteristics under different road environments and distraction patterns were analyzed in detail. For example, the probabilistic distribution of distraction parameters shows that the impact on reaction time is the greatest under distracted conditions on expressways with high traffic volume. This may be because, in such environments, drivers need to constantly react to rapid changes around them, such as sudden lane changes or emergency braking by other vehicles. Distractions can divert the driver's attention from the road, significantly increasing reaction time in high-speed and complex traffic environments, as drivers need more time to re-focus on the driving task. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Distraction** & **Dangerous** & **Serious Conflict** & **Mild Conflict** & **Safe** \\
**Fraction** & **(TTC \(<\) 1 s)** & **(1 s \(\leq\) TTC\(<\) 1.5 s)** & **(1 s \(\leq\) TTC \(<\) 2 s)** & **(TTC \(\geq\) 2 s)** \\ \hline
15\% & 4.52\% & 3.75\% & 4.59\% & 87.14\% \\
20\% & 7.24\% & 3.56\% & 5.25\% & 83.95\% \\
25\% & 8.60\% & 4.42\% & 5.07\% & 81.91\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Distribution of dangerous scenario levels in simulations. TTC: Time to Collision. In contrast, on expressways with low traffic volume, there might be fewer interactions between vehicles, and the driving task may not require as much continuous attention as in high-traffic environments. In these settings, distraction mainly affects drivers' perception of speed differences and following distances. This might be because at lower traffic volumes, drivers may more easily fall into their own rhythm, with perceived speed and following distance more reliant on their subjective assessment rather than frequently making decisions based on external stimuli. Distraction could distort this assessment, leading drivers to misjudge their relative speed and distance to the vehicle ahead, which could result in inappropriate driving responses in emergencies. On surface roads, due to the more complex environment, which includes more frequent intersections, pedestrian crossings, stopping and starting vehicles, as well as more road signs and traffic lights, drivers are required to allocate more attention to process diverse information and react accordingly. When drivers are distracted, the time needed to deal with these complex situations increases, thus lengthening the reaction time. Furthermore, as the traffic conditions on surface roads are more variable, drivers' perceptual biases exhibit a wider range of inconsistencies, manifested by a greater number of extreme values in the perception of speed differences and following distance. By applying the model in the simulation environment, effects of distraction on traffic flow were analyzed. The efficiency of traffic flow largely depends on drivers' reaction times and their ability to perceive speeds and following distances. Distraction typically increases reaction times, leading to delayed responses to changing traffic conditions. Additionally, perceptual deviation regarding speed and following distances may lead to less than ideal spacing between vehicles, creating a domino effect that disrupts traffic and reduces overall traffic efficiency.