17822969. Autonomous Driving Control Apparatus and Method Thereof simplified abstract (HYUNDAI MOTOR COMPANY)
Autonomous Driving Control Apparatus and Method Thereof
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Autonomous Driving Control Apparatus and Method Thereof - A simplified explanation of the abstract
This abstract first appeared for US patent application 17822969 titled 'Autonomous Driving Control Apparatus and Method Thereof
Simplified Explanation
The abstract describes an autonomous driving control apparatus that includes a sensor device, a memory, and a controller. The sensor device collects information about the surroundings of the autonomous vehicle using multiple sensors. The memory stores information about a high definition map around the vehicle. The controller classifies the sensors into sensor sets based on the collected information and the map data using a sensor set classification table. It also monitors the utilization rate of computational resources and the occupancy rate of the memory. Based on this monitoring, it calculates a determiner input drop rate and determines if there are available resources. If there are, it decides whether to allocate additional determiners and adjusts the autonomous driving determination period accordingly.
- The apparatus includes a sensor device with multiple sensors to gather information about the surroundings of the autonomous vehicle.
- It utilizes a high definition map stored in memory to classify the sensors into sensor sets based on the collected information and map data.
- The controller monitors the utilization rate of computational resources and the occupancy rate of the memory to determine if there are available resources.
- It calculates a determiner input drop rate to decide whether to allocate additional determiners for autonomous driving.
- The autonomous driving determination period can be adjusted based on the availability of resources.
Potential Applications
- Autonomous vehicles: This technology can be applied in autonomous vehicles to improve their ability to gather and process information from their surroundings, leading to more accurate and efficient autonomous driving.
- Smart transportation systems: The apparatus can be used in smart transportation systems to enhance the capabilities of vehicles in terms of navigation, obstacle detection, and decision-making.
Problems Solved
- Resource optimization: The apparatus helps optimize the utilization of computational resources and memory, ensuring efficient allocation and utilization of available resources.
- Sensor data classification: By classifying the sensors into sets based on the collected information and map data, the apparatus improves the accuracy and reliability of sensor data processing.
- Determiner allocation: The apparatus determines whether to allocate additional determiners based on resource availability, ensuring optimal performance in autonomous driving decision-making.
Benefits
- Improved autonomous driving: By efficiently utilizing available resources and accurately processing sensor data, the apparatus enhances the performance and reliability of autonomous driving systems.
- Resource optimization: The monitoring and allocation mechanisms of the apparatus help optimize the utilization of computational resources and memory, leading to improved efficiency and cost-effectiveness.
- Enhanced decision-making: The determiner allocation process ensures that the autonomous driving system has the necessary resources to make informed and reliable decisions, improving overall safety and performance.
Original Abstract Submitted
An autonomous driving control apparatus includes a sensor device obtaining information around an autonomous vehicle and including a plurality of sensors, a memory storing information about a high definition map around the autonomous vehicle, and a controller classifying the sensors into at least one sensor set based on the information around the autonomous vehicle and the information about the high definition map, using a sensor set classification table, monitoring a computational resource utilization rate and a resource occupancy rate of the memory, calculating a determiner input drop rate and determining whether there is an available resource, using the monitored computational resource utilization rate and the monitored resource occupancy rate, determining whether to additionally allocate at least one determiner using the determiner input drop rate and whether there is the available resource, and changing an autonomous driving determination period.
