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An IMPC based Parking Assistance System with Interactive Searching Function
ISSN: 0148-7191, e-ISSN: 2688-3627
To be published on October 22, 2019 by SAE International in United States
This paper summarizes progress and outcome from our research projects on IMPC-based parking management system, including parking motion planning and control strategy, as well as a searching strategy for parking spot. To predict future parking parameters, we proposed a practical framework which integrates anticipatory techniques with a model predictive approach that robustly models the stochastic parking environment. The framework is able to take into account the interactions between vehicle subsystems, and can optimize trajectory under complex traffic patterns in real-world scenarios. Adaptive model predictive control is utilized to optimally minimize a cost function regarding performance, energy efficiency and drivability with regard to surrounding vehicle states. Dynamic programming was used to solve the control objective under multiple constraints, which yielded superior performance in comparison with convex programming. An original navigation system was developed for leading user to the parking spot in case of forgetting exact location, which is characterized in that swift location and path are generated by BLE-based sensor fusion. After successful parking action, the system beacons the parking location and transmits data to mobile equipment of user, which serves as goal of searching task. Simulation results show promising expected cost minimization in typical parking environments under consideration of fuel efficiency, parking time and distance to destination. Meanwhile, the state of art park spot search module is able to shorten the time for drivers to locate their vehicle with positioning error of less than 1.5 meter.