Side collisions caused by sudden vehicle cut-ins comprise a significant proportion of traffic accidents. Due to the complex and dynamic nature of traffic environments, the warning algorithms in advanced driving assistant systems (ADAS) often misjudge and misdiagnose risk and omit necessary warnings, because they rely solely on the sensing information of the single vehicle equipped with ADAS and have limited insights from and communication with the surrounding vehicles and traffic environment. To improve the effectiveness of ADAS in cut-in scenarios, this study established a collision warning model in a vehicle-to-vehicle (V2V) communication environment. Firstly, based on the support vector machine-recursive feature elimination (SVM-RFE) lane-change intent-recognition model, the lane-change feasibility and the change rate of the lateral offset, the logical “and” was used to establish a lane-change behavior prediction model, and a trajectory prediction model was established based on the long short-term memory (LSTM). Then, based on the proposed comprehensive prediction model for lane-change behavior, the driving trajectory prediction model, and the oriented bounding box (OBB) detection algorithm, a collision warning model was established for a V2V environment. Finally, based on a driving simulation platform and a real-world vehicle test, a cut-in experiment in a V2V environment was designed and implemented. By comparing the warning confusion matrix and warning time, it was found that the proposed cut-in collision warning model is superior to the traditional collision warning model. The results of this study can provide new modeling ideas and a theoretical basis for ADAS to further optimize for a cut-in scenario.
Vehicle Trajectory Prediction and Cut-In Collision Warning Model in a Connected Vehicle Environment
IEEE Transactions on Intelligent Transportation Systems ; 23 , 2 ; 966-981
2022-02-01
5286481 byte
Article (Journal)
Electronic Resource
English
Vehicle collision early warning method based on vehicle trajectory prediction model
European Patent Office | 2024
|Vehicle Collision Warning Method Based on Trajectory Prediction
Springer Verlag | 2021
|Taylor & Francis Verlag | 2017
|Vehicle collision early warning method based on vehicle-road cooperation trajectory prediction
European Patent Office | 2023
|Vehicle trajectory prediction and collision warning for lane change conditions
Taylor & Francis Verlag | 2024
|