Vehicle Navigation Buffering for Obstacle-Aware Driver Intervention
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Solution Overview
Problem
Current autonomous vehicle navigation systems face challenges in ensuring safety and scalability, as they need to process various environmental data, adhere to liability constraints, and make real-time decisions while maintaining safety assurance standards, which is difficult to achieve with existing technologies.
Innovation Solution
The system employs multiple cameras and processing devices to analyze images and sensor data, including GPS information, to determine navigational actions such as braking and acceleration, while considering the capabilities of both the host vehicle and target vehicles, and implementing actions based on driving policies to ensure safe navigation and adherence to constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system processes multiple data sources (camera images, GPS, sensor data) in real-time to make navigational decisions, then navigation accuracy and safety are improved, but computational complexity and processing time increase
Solution Approach 1:
The system segments the complex navigation decision-making process into distinct functional modules: image capture device for visual data, GPS device for location data, sensor devices for environmental data, processing device for analysis, and control device for execution. Each module handles specific tasks independently, reducing overall system complexity while maintaining comprehensive safety assurance through coordinated operation of all segments.
2Reliability
If the system adheres to liability rules and safety constraints in navigational actions, then safety assurance is improved, but operational flexibility and response time may be reduced
Solution Approach 1:
The system performs preliminary actions by continuously monitoring the environment and pre-calculating safe navigational responses before critical situations arise. The processing device analyzes data from multiple sources in advance, identifies potential hazards, and prepares appropriate navigational actions that comply with liability rules, enabling rapid response when needed without sacrificing safety assurance.
3Measurement precision
If the system uses multiple cameras and sensors to capture environmental data, then measurement precision and safety are improved, but device complexity and cost increase
Solution Approach 1:
The system merges multiple data sources including camera images, GPS coordinates, and sensor readings into a unified environmental model through the processing device. By combining these diverse data streams and analyzing them collectively, the system achieves comprehensive measurement precision for navigational decision-making while managing device complexity through integrated processing rather than separate analysis of each sensor.
Data Source
AI summary
A system for a host vehicle includes a processor programmed to receive, from an image capture device, an image representative of an environment of the host vehicle, detect at least one obstacle in the environment of the host vehicle based on an analysis of the at least one image, determine a velocity of the host vehicle and a predicted path for the host vehicle, monitor a driver input to at least one of a throttle control, a brake control, or a steering control associated with the host vehicle, and determine whether the driver input would result in the host vehicle navigating within a proximity buffer relative to the at least one obstacle, wherein the proximity buffer is determined based on the determined velocity, a maximum acceleration capacity of the host vehicle, and a maximum braking capacity of the host vehicle, and a reaction time associated with the host vehicle.