Abstract
Lane-Changing Decision (LCD) behavior is complex, dangerous, and varied by the Driver's Psychology (DP) and Driving Style (DS). For lacking the consideration of DP and DS, the existing LCD models cannot predict the LCD process varying with the drivers and traffic conditions accurately. To deal with the problems, a new LCD model coupling DP and DS, named DP&DS-LCD, is put forward. In the model, a psychological field model is constructed to represent the DP effect on the scene vehicles. And then, K-means and K-Nearest Neighbor (KNN) algorithm are respectively adopted in learning and recognition phases to recognize the current driving style pattern. Finally, based on the DP and DS, the multi-Grained Cascade Forest (gcForest) algorithm is applied to predict the LCD behavior. In experiments, DP&DS-LCD is compared with other three LCD models by using the opening I-80 database from Next Generation Simulation project (NGSIM). And the results showed that the DP&DS-LCD model achieved the best performance. Therefore, the DP&DS-LCD model is effective and could provide support for the decision of autonomous vehicles by predicting the surrounding vehicles' Lane-Changing (LC) behavior.
Highlights
With the development of autonomous driving technology, the mixed driving of autonomous vehicles and artificial vehicles will become a common situation in the future
The accuracy of Driver’s Psychology (DP)&Driving Style (DS)-Lane-Changing Decision (LCD) model is the average accuracy under the five time-windows
The present LCD researches mostly focused on the objective LC traffic conditions, few considered the DP and DS simultaneously
Summary
With the development of autonomous driving technology, the mixed driving of autonomous vehicles and artificial vehicles will become a common situation in the future. In order to ensure the safe driving of autonomous vehicles, it is important to predict the LC behavior of the surrounding artificial vehicles accurately. For DLCD, it is implemented to change the vehicle’s motion process from the current lane to the target lane for the better driving speed. The LCD problem on DLCD is addressed. LCD procedure could be divided into four stages: (1) LC intention generation; (2) target lane selection; (3) LC condition judgment; (4) LC execution. The LC intention is generated by drivers and
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