To alleviate the driver's nervousness, a lane‐keeping algorithm based on scene analysis is proposed. From the driver's point of view, two key parameters are studied, which are the distance between the traffics car and the lane centreline of the host car, and the time‐gap difference between the host car and the traffic car. The designed scene analysis algorithm is mainly based on these two parameters to screen out dangerous traffic vehicles. To ensure driving comfort when driving states change, a five‐power polynomial is used to plan a smooth path based on the location of the dangerous traffic vehicle. Considering the real‐time and robustness of the control algorithm, this study proposes a feedforward and feedback control architecture combined with the preview‐following theory. To verify the algorithm, a variety of typical tests are designed. The experimental results show that the algorithm can make the vehicle smoothly follow the planning path.
Lane‐keeping system design considering driver's nervousness via scene analysis
IET Intelligent Transport Systems ; 14 , 10 ; 1171-1182
2020-10-01
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
traffics car , traffic car , feedback , time‐gap difference , road safety , road traffic , collision avoidance , lane‐keeping system design , automobiles , traffic engineering computing , driving comfort , control algorithm , feedforward , road vehicles , driving states change , feedback control architecture , driver , mobile robots , path planning , lane‐keeping algorithm , dangerous traffic vehicle , designed scene analysis algorithm , host car , robustness , lane centreline
Lane-keeping system design considering driver's nervousness via scene analysis
IET | 2020
|A self-learning lane change motion planning system considering the driver’s personality
SAGE Publications | 2021
|