关键词: 无人驾驶车辆；驾驶行为；预测模型；驾驶策略；轨迹映射

Abstract: Predicting the driving behavior of surrounding vehicles is of great significance to improving the safety of driverless cars. This paper divides the driving behavior prediction model in driverless cars into three aspects: description of driving behavior, driving behavior prediction algorithm, and formulation of driving strategy. It sorts out the typical driving behavior prediction models in current driverless vehicles. This article first introduces three driving behavior description methods, subjective definition, finite state machine, and trajectory characteristics, and summarizes the characteristics of various driving behavior prediction models. It points out the limitations of the three typical driving behavior description methods in the actual driving environment. In complex scenes, Hidden Markov model is difficult to classify hidden states and the determination of parameters is too complicated. Finally, the possible application of computer vision in driving behavior prediction models in the future is prospected. This paper summarizes the typical methods of current driving behavior prediction, which provides a reference for data-driven driving behavior prediction research combined with computer vision, and helps researchers to further familiarize themselves with related fields.

Key words: Driverless vehicle; Driving behavior; Prediction model; Driving strategy; Trajectory mapping