Assisted Parking Rollback Control Using Learned Vehicle Paths
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle control systems lack the ability to seamlessly transition between manual and autonomous driving modes based on real-time driving environment information, leading to inefficiencies and safety concerns during parking and navigation.
Innovation Solution
A vehicle control device and method that utilizes a combination of sensors and communication systems to switch between manual and autonomous modes based on driving environment information, using a user interface, object detection, and communication apparatus to enable autonomous driving by learning from previous driving experiences and adapting to changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle operates in manual driving mode, then the driver has full control over the vehicle, but the driver must constantly monitor and intervene in driving tasks, increasing mental workload and reducing convenience
Solution Approach 1:
The system enables autonomous driving capability where the vehicle performs driving tasks automatically without continuous driver intervention. The controller executes autonomous driving algorithms to handle steering, acceleration, and braking, freeing the driver from constant monitoring while maintaining safety through multiple sensor systems.
Solution Approach 2:
The system performs preliminary detection and planning actions through multiple sensors (cameras, LIDAR, radar) to identify obstacles, pedestrians, and road conditions before executing driving maneuvers. This advance preparation allows seamless transition between manual and autonomous modes by having the system ready to take control when needed.
2Adaptability or versatility
If the vehicle switches between manual and autonomous modes, then adaptability to different driving conditions is improved, but system complexity and difficulty of control increase
Solution Approach 1:
The system dynamically adjusts between manual and autonomous driving modes based on real-time environmental conditions and sensor data. The controller continuously evaluates situational parameters and automatically transitions modes when conditions warrant, making the system adaptable without requiring complex manual switching mechanisms.
Solution Approach 2:
The control system integrates multiple functions including obstacle detection, path planning, vehicle control, and mode management into a single unified controller. This multi-functional approach handles both manual and autonomous operations through one system, reducing overall complexity compared to separate dedicated systems for each mode.
3Reliability
If autonomous driving is implemented, then driving efficiency and safety are improved through learned patterns, but the system requires extensive sensing and communication equipment, increasing device complexity
Solution Approach 1:
The system combines multiple sensing technologies (cameras, LIDAR, radar, ultrasonic sensors) and communication systems into an integrated sensor fusion architecture. The controller processes data from all these sources simultaneously, creating a comprehensive environmental model that improves safety while managing complexity through unified processing rather than separate independent systems.
Solution Approach 2:
The system implements continuous feedback loops where sensor data is constantly monitored, analyzed, and used to adjust driving decisions in real-time. The controller receives feedback from multiple sensors about obstacles, road conditions, and vehicle state, and automatically adjusts autonomous driving parameters to maintain safety and efficiency.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method for assisted parking of a vehicle performed by a parking control device. The method includes: determining a current position of a vehicle based on at least one of GPS information or environment information of the vehicle; generating traveling map information during manual driving of the vehicle, the traveling map information including a traveling path of the vehicle from the current position of the vehicle, based on at least one user input received through a vehicle manipulation device and at least one sensor value acquired through at least one sensor; and transmitting, based on receiving a rollback request signal, a rollback control signal that causes the vehicle to autonomously drive in a reverse direction along at least part of the traveling path from a rollback starting position of the vehicle.