期刊
SUSTAINABILITY
卷 15, 期 16, 页码 -出版社
MDPI
DOI: 10.3390/su151612366
关键词
force/tactile auxiliary steering control; virtual force guidance; vehicle path planning; RRT algorithm; auxiliary safety driving
This study proposes an auxiliary steering control system with force/tactile guidance (ASCFT) to address the problem of complex road conditions leading to traffic accidents. The system combines the manipulative force of the driver and a virtual guidance force to provide a sense of steering force based on road information, achieving auxiliary safety driving.
The rapid development of the automobile industry has resulted in the development of many vehicles, increased traffic, and frequent accidents. The complexity of road conditions is a major contributor to the occurrence of traffic accidents. Drivers are distracted and hence unable to fully observe all road information and make optimal and timely driving decisions. This study proposes an auxiliary steering control system with force/tactile guidance (ASCFT) and its corresponding control strategy to address this problem. We combined vehicle autonomous path planning based on road condition information and the human-machine sharing control strategy, which integrated the manipulative force of the driver and a virtual guidance force on the steering wheel. Consequently, the ASCFT eliminated the mechanical connection between the steering wheel and the steering wheels in favor of a force/tactile-assisted steering structure, providing the driver with a sense of steering force based on road information. Additionally, we proposed a smooth vehicle trajectory optimization method based on the improved RRT algorithm and a path-following controller based on the forecast information to achieve auxiliary safety driving. The ASCFT's performance was confirmed through constructing a fixed-base simulator experimental platform with the ASCFT. The results revealed that at the vehicle speed of 60 km/h and a handwheel rotation of 60 & DEG;, the steering wheel was instantly released and turned back in about 3.5 s. Furthermore, predictive haptic feedback warned the driver of an upcoming obstacle.
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