## 4 Case Study
### Analysis of Influencing Factors  
AVs need to enter the dedicated lane through lane-changing behavior. Through progressive research in the field of ITS technology, it has been found that traditional single-vehicle intelligent technology makes it difficult to achieve full autonomous driving. Therefore, roadside infrastructure and road pavement markings are needed to help intelligent vehicles achieve autonomous driving functions in the initial stage of autonomous driving technology implementation. At the same time, AVs and HDVs will form a mixed traffic flow for a long time. In order to encourage the development of AVs and to ensure the efficiency of the mixed traffic flow, it is necessary to set up dedicated lanes for AVs on existing highways. Since AVs are randomly distributed in lanes before they enter the highway sections where the dedicated lane exists, AVs need to enter the dedicated lane through lane-changing behaviors. Setting a buffer zone in the adjacent lane can guarantee a safe lane change environment, as shown in Figure 5.  
A buffer zone is a special section located adjacent to an autonomous driving dedicated lane that is closed to HDVs. The buffer zone can be set up as colored section of the pavement to facilitate recognition for AVs using computer vision. When the vehicle travels to the beginning of the buffer zone, the AV receives the lane change command and enters the lane change preparation stage. If the vehicle shows lateral displacement, it indicates that it has \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Meaning of Variables** & **Variables** & **Meaning of Variables** & **Variables** \\ \hline Speed in preparation stage & \(X_{1}\) & Duration in execution stage & \(X_{10}\) \\ Average acceleration in preparation stage & \(X_{2}\) & Speed in adjustment stage & \(X_{11}\) \\ Spacing in preparation stage & \(X_{3}\) & Average acceleration in adjustment stage & \(X_{12}\) \\ Headway in preparation stage & \(X_{4}\) & Spacing in adjustment stage & \(X_{13}\) \\ Duration in preparation stage & \(X_{5}\) & Headway in adjustment stage & \(X_{14}\) \\ Speed in execution stage & \(X_{6}\) & Duration in adjustment stage & \(X_{15}\) \\ Average acceleration in execution stage & \(X_{7}\) & Distance between target and rear vehicle & \(X_{16}\) \\ Spacing in execution stage & \(X_{8}\) & Rear vehicle speed in target lane & \(X_{17}\) \\ Headway in execution stage & \(X_{9}\) & Speed at the end of adjustment stage & \(X_{18}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Diagram of relevant variables. Figure 5: Diagram of the buffer zone for lane-changing behavior. entered the execution stage. When the center of the vehicle crosses over to the dedicated lane, it indicates that it has entered the adjustment stage. The lane-changing behavior ends when there is no more lateral displacement of the vehicle. In the process of AVs driving into the dedicated lane, the buffer zone not only reminds and guides the vehicles into the dedicated lane, but also protects the AVs during the whole process of lane-changing behavior and avoids the interference of the HDVs. As a result, by studying the influencing factors of lane-changing behavior and exploring how to shorten the longitudinal distance of the lane-changing process, effective suggestions can be provided for setting the section length of the buffer zone. To investigate the factors influencing lane-changing behavior, the authors used principal component analysis to process the lane-changing behavior data. SPSS was used to perform the principal component analysis of 455 standardized vehicles' lane-changing information. Related factors are dimensionally reduced to obtain the correlation coefficient matrix, KMO Bartlett test, and principal component analysis results. Next, PCA results will be explained and the influencing factors of lane-changing behavior will be summarized. First, the KMO Bartlett method was used to test the distribution and independence of the variables to determine the suitability of the data for PCA.