# A Method of Intelligent Driving-Style Recognition Using Natural Driving Data
## 4 Result
### Data Analysis
#### 4.2.2 Principal Component Analysis  
Before PCA, the Kaiser-Meyer-Olkin (KMO) test results of car-following and lane-changing characteristic parameter matrices are 0.797 and 0.771. [PERSON]'s spherical test results are both less than 0.001, which is suitable for PCA. After standardizing the characteristic parameter matrix, the principal components with a cumulative contribution rate exceeding 80% are selected as the dimension reduction result, and 6 and 7 principal components of car-following and lane-changing are selected as dimension reduction results, as shown in Tables 2 and 3, respectively. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Number** & **Characteristic Parameter** & \multicolumn{5}{c}{**Principal Component**} \\  & **1** & **2** & **3** & **4** & **5** & **6** \\ \hline X1 & Maximum speed & 0.261 & 0.057 & 0.084 & \(-\)0.318 & \(-\)0.218 & 0.228 \\ X2 & Mean speed & 0.224 & \(-\)0.073 & 0.113 & \(-\)0.364 & \(-\)0.399 & 0.018 \\ X3 & Standard deviation of speed & 0.136 & 0.274 & 0.026 & \(-\)0.035 & 0.246 & 0.607 \\ X4 & Maximum absolute value of acceleration & 0.258 & 0.159 & \(-\)0.150 & 0.198 & \(-\)0.125 & \(-\)0.074 \\ X5 & Mean value of acceleration absolute value & 0.304 & \(-\)0.182 & 0.040 & 0.110 & 0.034 & 0.096 \\ X6 & Standard deviation of absolute acceleration value & 0.281 & \(-\)0.015 & \(-\)0.074 & 0.310 & \(-\)0.116 & 0.077 \\ X7 & Maximum acceleration & 0.243 & 0.128 & \(-\)0.142 & 0.112 & \(-\)0.116 & 0.087 \\ X8 & Average acceleration & 0.281 & \(-\)0.151 & 0.032 & 0.077 & 0.052 & 0.221 \\ X9 & Maximum deceleration & \(-\)0.231 & \(-\)0.164 & 0.129 & \(-\)0.203 & 0.113 & 0.274 \\ X10 & Average deceleration & \(-\)0.268 & 0.153 & 0.002 & \(-\)0.156 & \(-\)0.033 & 0.055 \\ X12 & Car-following time & 0.024 & 0.469 & \(-\)0.295 & \(-\)0.159 & 0.155 & \(-\)0.040 \\ X13 & Distance traveled during car-following time & 0.118 & 0.423 & \(-\)0.246 & \(-\)0.297 & \(-\)0.017 & \(-\)0.050 \\ X15 & Mean space headway & 0.101 & 0.185 & 0.472 & \(-\)0.111 & \(-\)0.332 & \(-\)0.221 \\ X16 & Standard deviation of space headway & 0.073 & 0.268 & 0.433 & \(-\)0.011 & \(-\)0.045 & 0.238 \\ X18 & Mean time headway & \(-\)0.072 & 0.263 & 0.448 & 0.201 & \(-\)0.009 & \(-\)0.265 \\ X19 & Standard deviation of time headway & \(-\)0.055 & 0.257 & 0.284 & 0.374 & 0.316 & 0.123 \\ X23 & Average value of positive jerk & 0.271 & \(-\)0.238 & 0.139 & \(-\)0.071 & 0.218 & \(-\)0.039 \\ X24 & Average value of negative jerk & \(-\)0.259 & 0.231 & \(-\)0.158 & 0.113 & \(-\)0.256 & 0.023 \\ X25 & Maximum positive jerk & 0.180 & 0.057 & 0.031 & \(-\)0.184 & 0.442 & \(-\)0.329 \\ X26 & Maximum negative jerk & \(-\)0.183 & \(-\)0.022 & \(-\)0.103 & 0.328 & \(-\)0.352 & 0.225 \\ X27 & Rapid acceleration times & 0.252 & 0.082 & \(-\)0.093 & 0.158 & \(-\)0.032 & \(-\)0.021 \\ X28 & Rapid deceleration times & 0.233 & 0.089 & \(-\)0.097 & 0.208 & \(-\)0.049 & \(-\)0.261 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Principal component kernel load matrix of car-following. According to Table 2, it can be seen that PC1 has large correlation coefficients with X1, X5, X6, X8, X23, and X27\(\sim\)X28 in the original feature parameters. It mainly represents the longitudinal motion characteristics of the driver's own car, and it is named the \"longitudinal factor\". PC2 shows relatively high correlation coefficients with X12 (0.469) and X13 (0.423). It mainly represents the overall car-following situation and is named the \"longitudinal displacement factor\". The correlation coefficients between PC3 and X15-X16 and X18-X19 are large. It mainly represents the correlation between the front and rear cars in the car-following state and is named the \"longitudinal correlation factor\". As shown in Table 3, the correlation coefficients between PC1 and the variables X5-X6, X8, and X23-X24 are relatively large. This mainly represents the change in speed and acceleration in the longitudinal movement, named PC1 as the \"longitudinal speed change factor\".