Autonomous Vehicle Sensor Fusion for Blind Spot Detection
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Solution Overview
Problem
Autonomous driving systems face challenges in safely navigating complex environments with many obstacles and pedestrians, such as public housing or mart parking lots, due to limitations in real-time situational adaptation and lack of effective communication with surrounding vehicles.
Innovation Solution
An autonomous driving control apparatus that includes a communication device and controller to exchange information with parked vehicles, enabling sensors to detect and respond to surrounding obstacles, and a display device to alert users of potential hazards, allowing for controlled autonomous navigation in crowded spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous driving systems use existing sensor limitations in crowded parking lots, then device complexity is reduced, but safety and reliability deteriorate due to inability to detect obstacles in blind spots
Solution Approach 1:
The patent merges sensor resources from multiple parked vehicles to create a collective detection network. The autonomous vehicle communicates with surrounding parked vehicles to access their sensor data, effectively combining detection capabilities without adding physical sensors to the autonomous vehicle itself. This resolves the contradiction by improving safety through enhanced obstacle detection while avoiding the complexity of installing additional sensors.
Solution Approach 2:
The patent introduces communication devices and control devices as intermediaries between the autonomous vehicle and parked vehicles. These intermediaries facilitate the exchange of sensor information and enable the autonomous vehicle to access blind spot data from surrounding vehicles. This mediator approach improves detection reliability without directly increasing the autonomous vehicle's hardware complexity.
2Measurement precision
If autonomous vehicles navigate crowded spaces with limited sensor coverage, then ease of operation is maintained, but measurement precision deteriorates due to blind spots in obstacle detection
Solution Approach 1:
The patent transitions from a single-vehicle sensor perspective to a multi-vehicle collaborative detection dimension. By accessing sensor data from multiple parked vehicles surrounding the autonomous vehicle, the system creates a three-dimensional detection network that eliminates blind spots. This dimensional expansion improves measurement precision without adding complex processing equipment to the autonomous vehicle.
Solution Approach 2:
The patent makes sensor resources universal by allowing them to serve multiple vehicles. Sensors on parked vehicles that would normally only detect for their own vehicles are made available to the autonomous vehicle through communication interfaces. This multi-functionality approach improves detection precision across all vehicles in the network without requiring each vehicle to have dedicated sensors for every direction.
3Adaptability or versatility
If autonomous vehicles do not communicate with surrounding vehicles, then device complexity is reduced, but adaptability to dynamic environments deteriorates
Solution Approach 1:
The patent implements feedback loops where the autonomous vehicle continuously receives sensor information from parked vehicles and adjusts its navigation accordingly. The control device processes incoming data and modifies driving decisions in real-time based on detected obstacles and environmental changes. This feedback mechanism enhances adaptability to dynamic environments while using standard communication and control components.
Solution Approach 2:
The patent enables preliminary detection of potential obstacles by accessing sensor data from parked vehicles before the autonomous vehicle encounters blind spots. By proactively receiving information about objects in areas not directly visible to the autonomous vehicle's sensors, the system can prepare appropriate responses in advance, improving adaptability without requiring complex real-time processing equipment.
Data Source
AI summary
An autonomous driving control apparatus for controlling autonomous driving around another vehicle that is parked includes a controller configured to receive information about an object sensed by sensors provided in one or more other vehicles from the one or more other vehicles, through a communication device provided in an autonomous vehicle. The controller is further configured to control autonomous driving around the one or more other vehicles based on the received information. The autonomous driving control apparatus allows an autonomous vehicle to safely travel in a space with many persons, such as in a public housing parking lot, a mart parking lot, or the like.