## 3 Results and Analysis
### Lane Changing Characteristics
#### 3.3.3 Accepted Gap  
Gap acceptance, a key factor in LC modeling, reflects drivers' safety and smoothness expectations during LC decisions. Statistical tests show a significant influence of CD and TC on gap acceptance, with both main (\(p<0.001\)) and interactive effects (\(p<0.001\)) observed. Figure 16 displays the distribution of accepted and critical gaps, illustrating the impact of CD and TC interaction on gap selection. As CD decreases, drivers tend to choose smaller gaps for LC, indicative of a proactive LC strategy. For instance, in 100 m CD scenarios, about 30% of vehicles opt for gaps of less than 3 s for LC completion (Figure 16a). Conversely, at a 1000 m CD, such choices are much rarer, seen in under 5% of samples. These patterns highlight a heightened urgency for LC in small spacing sections.  
Table 10 further examines the variance in the accepted gaps due to changes in CD across different LOS. At the first service level, the accepted gap in different CDs is similar, with only a 0.26 s difference between the 100 m and 1000 m samples. In contrast, at the 2 nd and 3 rd LOS, these differences expand to 0.67 s and 0.91 s. As traffic volume escalates, intergroup differences for various CDs widen, particularly elevating LC difficulties in shorter spacing sections under heavy traffic.  
Figure 17 further details the joint distribution relationship between the accepted gaps and MLC characteristics. When the gap drops below 3 s, the average LCA increases to 17.6\({}^{\circ}\), and the average LCD drops to about 3.8 s. It can be inferred that drivers on larger spacing sections with low traffic volumes benefit from more time and space to assess and select suitable gaps. Conversely, on shorter spacing sections with high traffic volumes, drivers are compelled to choose smaller gaps and expedite LC completions. This change  
Figure 15: Joint distribution between MLCD, MLCL, and MLCA.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**CD**} & \multirow{2}{*}{**CD**} & \multicolumn{2}{c}{**MLCA (\({}^{*}\))**} & \multicolumn{2}{c}{**MLCD (s)**} & \multicolumn{2}{c}{**MLCL (m)**} \\
**Group 1** & & **Group 2** & **Difference** & \(p\)**-Value** & **Difference** & \(p\)**-Value** & **Difference** & \(p\)**-Value** \\ \hline \multirow{6}{*}{1000 m} & 100 m & **6.26 \({}^{*}\)** & 0.000 & **\(-\)2.56** & 0.000 & **51.04** & 0.000 \\  & 300 m & **5.69** & 0.000 & **\(-\)2.23** & 0.000 & **43.65** & 0.000 \\  & 500 m & **4.41** & 0.000 & **\(-\)1.23** & 0.000 & **27.46** & 0.000 \\  & 700 m & 0.68 & 0.064 & \(-\)0.15 & 0.147 & 4.04 & 0.079 \\  & GDS & \(-\)0.30 & 0.805 & **0.17** & 0.047 & \(-\)1.31 & 0.570 \\ \hline \multirow{6}{*}{300 m} & 100 m & 0.58 & 0.147 & **\(-\)0.33** & 0.000 & **7.38** & 0.001 \\  & 500 m & **\(-\)1.27** & 0.000 & **1.00** & 0.000 & **\(-\)16.19** & 0.000 \\ \cline{1-1}  & 700 m & **\(-\)5.01** & 0.000 & **2.08** & 0.000 & **\(-\)39.61** & 0.000 \\ \cline{1-1}  & 1000 m & **\(-\)5.69** & 0.000 & **2.23** & 0.000 & **\(-\)43.65** & 0.000 \\ \cline{1-1}  & GDS & **\(-\)5.98** & 0.000 & **2.40** & 0.000 & **\(-\)44.96** & 0.000 \\ \hline \hline \end{tabular} \({}^{*}\) The bold terms indicate that the difference between the groups is significant at the 95% level.  
\end{table}
Table 9: [PERSON]’s test for intergroup differences in MLC indicators.