Vehicle Parking Guidance System Using Driver Pattern Learning
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Solution Overview
Problem
Conventional smart parking assistance systems (SPAS) are inefficient in dense and crowded areas, requiring a long time to park and are difficult to use after the driver leaves the vehicle, especially in city environments.
Innovation Solution
A system and method that utilizes a sensor unit, database unit, and controller to assess parking difficulty by generating parking trajectories based on sensor data and driver parking patterns, providing information to the driver through an output unit, including camera, ultrasonic, radar, LiDAR, and GPS sensors, and updating parking pattern data after parking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional smart parking assistance systems are used in dense and crowded areas, then parking assistance function is provided, but parking time is excessively long and operation becomes difficult after driver leaves vehicle
Solution Approach 1:
The system performs preliminary actions by pre-calculating multiple parking trajectories (first parking trajectory based on sensor data, second parking trajectory based on driver patterns) and pre-assessing parking difficulty before the driver actually attempts to park. This allows the driver to receive advance guidance on the easiest parking space to use, reducing on-site decision time and operational difficulty.
Solution Approach 2:
The system enables self-service by automatically sensing the parking environment, generating parking trajectories, assessing parking difficulty, and providing guidance information without requiring the driver to manually control steering or make complex decisions. The driver only needs to control shifting while the system handles trajectory planning and provides real-time guidance.
2Adaptability or versatility
If conventional smart parking assistance systems are used, then parking assistance is provided, but the system is impractical for use after driver gets out of vehicle in crowded city sections
Solution Approach 1:
The system is designed to operate autonomously after the driver exits the vehicle. The sensor unit continuously senses the parking environment, the controller automatically generates and compares parking trajectories, and the output unit provides real-time guidance information to the driver's mobile device, enabling fully hands-free operation in crowded city sections.
Solution Approach 2:
The system uses a mobile device as an intermediary to communicate parking guidance information between the vehicle's sensor unit and controller and the driver. This allows the driver to receive real-time parking assistance information without needing to be physically present in the vehicle, making the system practical for use after driver exits.
3Adaptability or versatility
If conventional parking assistance systems are used, then basic parking control is achieved, but the system lacks personalized adaptation to individual driver parking patterns
Solution Approach 1:
The system performs preliminary learning of driver parking patterns during normal driving operations before needing to provide personalized assistance. The controller stores steering angle, braking force, and shifting pattern data in a database, building a personalized profile that enables customized trajectory generation without adding operational complexity for the driver.
Solution Approach 2:
The system creates a digital copy of the driver's parking behavior patterns by storing and analyzing historical steering, braking, and shifting data. This copied behavioral model is then used to generate personalized parking trajectories that match the driver's preferred style, providing adaptability without requiring the driver to manually configure settings.
Data Source
AI summary
Disclosed is a system of providing a parking guidance service of a vehicle including a sensor unit including a plurality of sensors configured to sense an environment around the vehicle and a parking space, a database unit configured to store parking pattern data of a driver, a controller configured to determine a parking difficulty of the parking space based on information sensed by the sensor unit and parking pattern data of the driver, stored in the database unit, and an output unit configured to provide information on the parking difficulty of the parking space, determined by the controller.