# Simulation-Oriented Analysis and Modeling of
## 6 Micro-Simulation Implementation
### Pre-Crash Scenario Simulation  
For many classical car-following models like IDM, generating actual accidents or dangerous scenarios is challenging due to the model's inherent structural limitations. Given the non-zero minimum spacing at standstill in the IDM requires the driver's desired following distance to be greater than zero, the IDM inherently cannot simulate collision scenarios. This paper incorporates distractions into the IDM to introduce more dangerous reaction times and perception deviation, thereby increasing interference in traffic flow. This approach enhances the simulation's ability to produce more dangerous scenarios. This section selects Time to Collision (TTC) to demonstrate the changes in traffic safety caused by distraction, thereby exploring the simulation capability of IDM-distraction for pre-crash scenarios [52]. TTC is defined as the time constant at which a follower would collide with  
\begin{table}
\begin{tabular}{c c} \hline
**Distraction Fractions** & _p-Value_ \\ \hline
15\% & \textless{}0.001 \\
20\% & \textless{}0.001 \\
25\% & \textless{}0.001 \\ \hline \end{tabular}
\end{table}
Table 6: Significance analysis of the impact of distraction on different road sections.  
Figure 9: Impact of distraction fractions on different road segments.  
his leader given the speeds of both vehicles stay constant, and is a longitudinal indicator often used to measure the danger of a scenario.  
\[\text{TTC}_{n}(t)=\frac{S_{n}(t)}{\Delta V_{n}(t)},\Delta V_{n}(t)>0 \tag{9}\]  
Table 7 indicates that when the fraction of distracted drivers is 25%, the fraction of dangerous scenarios (TTC \(<\) 1 s) is the highest, at 8.60%. Then, as the distraction fraction decreases, the fraction of dangerous scenarios also declines. For serious conflicts (1 s \(\leq\) TTC \(<\) 1.5 s), the scenario fraction is still the largest when the distraction fraction is 25%. The fraction of safe scenarios (TTC \(\geq\) 2 s) decreases as the distraction fraction increases.  
For comparative analysis, we selected 360 car-following pairs from a naturalistic driving dataset and calculated the distribution of their TTC. Statistical analysis shows that the fraction of dangerous scenarios in naturalistic driving dataset is 8.11%, the fraction of serious conflicts is 0.78%, the fraction of mild conflicts is 1.10%, and the fraction of safe scenarios is 90.01%. Comparison reveals that the fraction of dangerous scenarios generated in simulation experiments when the distraction fraction is 15% is closest to real scenarios. However, the fractions of serious and mild conflicts in simulation experiments are both higher than in real scenarios, and the fraction of safe scenarios is lower than in real scenarios.  
This may be because the driver model used in the simulation does not simulate the evasive actions taken by drivers in dangerous situations (nor the contributions of any active safety systems with which vehicles may be equipped), leading to an overestimation of the fraction of conflict scenarios. Moreover, distracted behavior in the real world may be more random and irregular; however, the simulation of types of distraction in simulation experiments is limited.