Predictive Control Strategy for Driving of Intelligent Vehicle System against the Parking Slots
Deepak Kumar Dewangan, Satya Prakash Sahu
Abstract
Autonomous parking capability is one of the major applications of autonomous vehicles in the automobile industry. The standard vehicle parking requires acceleration, braking, and steering control to park the vehicle into the particular parking space. However, a small amount of driving error in any of the mentioned control towards the parking may produce hazardous situations and may lead to road accidents. Apart from the standard scenario, parallel parking and reverse parking are too risky application areas in which controlling computation has to be very specific. For the demanding market of autonomous vehicles, this application requires pin-point trajectory planning which may assist the parking not only in the standard slot but also covers parallel and reverse parking. In the proposed approach, a model-based scheme is being represented with the motion planning and cost function calculation to ensure the trajectory planning with minimum error. The cost function defined in the scope determines the steering angle and delivers the trajectory in which a vehicle should drive. Further, the location mapping of available parking space is computed by the vision sensor approach in the design which provides a low-cost solution and confirms the localization of the vehicle into the parking slot. The idea is represented using simulation and confirms the parking against the mentioned scheme.