Research on Recognition of Road Hypnosis in the Typical Monotonous Scene

Abstract

Road traffic safety can be influenced by road hypnosis. Accurate detection of the driver’s road hypnosis is a very important function urgently required in the driver assistance system. Road hypnosis recurs frequently in a certain period, and it tends to occur in a typical monotonous scene such as a tunnel or a highway. Taking the scene of a tunnel or a highway as a typical example, road hypnosis was studied through simulated driving experiments and vehicle driving experiments. A road hypnosis recognition model based on principal component analysis (PCA) and a long short-term memory network (LSTM) was proposed, where PCA was used to extract various parameters collected by the eye tracker, and the LSTM model was constructed to identify road hypnosis. The accuracy rates of 93.27% and 97.01% in simulated driving experiments and vehicle driving experiments were obtained. The proposed method was compared with k-nearest neighbor (KNN) and random forest (RF). The results showed that the proposed PCA-LSTM model had better performance. This paper provides a novel and convenient method to realize the driver’s road hypnosis detection function of the intelligent driver assistance system in practical applications.

A Recognition Method for Road Hypnosis Based on Physiological Characteristics

“…In our published work [ 27 ], eye-movement information is used to identify road hypnosis. In the previous study, the characteristic parameters of road hypnosis are determined by observing the ECG signals of drivers.…”

“…In our previous work [ 27 ], drivers’ eye movement characteristic parameter has been used to train the identification model for road hypnosis. Although road hypnosis can be accurately identified with this model, the interference caused by cognitive distraction cannot be excluded.…”

Road Hypnosis Detection using Lane Detection

“…Literature Review [1] The discussion revolves around a study focused on differentiating between normal driving and road hypnosis states using machine learning techniques. Fifty test subjects participated in simulated and realworld vehicle driving trials where eye movement data was recorded in repetitive scenarios.…”