Autonomous Vehicle Visibility Assessment for Adaptive Driving Control
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating environments with varying visibility conditions, which can affect their driving operations, leading to safety and efficiency issues.
Innovation Solution
An in-vehicle control computer determines visibility conditions using sensors and adjusts driving-related variables such as speed, distance, and navigation based on light levels, object detection, weather, and location to ensure safe operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous vehicles operate in environments with varying visibility conditions, then the vehicle can navigate diverse environments, but safety and efficiency deteriorate due to inadequate adaptation to visibility changes
Solution Approach 1:
The system dynamically adjusts driving operations by continuously monitoring visibility conditions through sensors and modifying driving variables in real-time. The control computer adapts speed, distance, and navigation parameters based on current visibility assessments, transforming the static driving system into a dynamic one that responds to environmental changes.
Solution Approach 2:
The patent changes key driving parameters (speed, distance, navigation) based on visibility condition assessments. When visibility deteriorates, the system automatically reduces speed, increases following distance, and adjusts navigation decisions, thereby maintaining safety margins across varying environmental conditions.
2Reliability
If the vehicle adjusts driving operations based on visibility conditions, then safety improves, but system complexity increases due to additional sensing and control mechanisms
Solution Approach 1:
The system uses existing autonomous vehicle sensors (cameras, LIDAR, radar) for multiple purposes: primary navigation and obstacle detection, plus visibility condition assessment. By making the sensing system multi-functional, the patent avoids adding dedicated visibility sensors while still achieving enhanced safety through visibility-based adaptation.
Solution Approach 2:
The control computer automatically assesses visibility conditions and adjusts driving operations without requiring external intervention or complex additional subsystems. The system serves itself by using its existing sensing capabilities to monitor environmental conditions and autonomously modifying its driving behavior accordingly.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the safety and efficiency of autonomous driving by adapting to different visibility conditions, ensuring appropriate driving behaviors in various environments.
Implementation Method 1
performing a first determination, based on sensor data provided by a light sensor, that an amount of light of the environment is less than a threshold value
Implementation Method 2
performing a first determination, based on an image provided by a camera, that an amount of light of the environment is less than a threshold value
Implementation Method 3
performing a first determination, based on information provided by a global positioning system (GPS) transceiver located on the autonomous vehicle, that the autonomous vehicle is operating within a range of a first distance and a second distance of a traffic intersection
Implementation Method 4
performing a first determination, based on a point cloud data provided by a light detection and ranging (LiDAR) sensor, that a number of lane markers located on a road within a distance of a location of the autonomous vehicle
Data Source
AI summary
Techniques are described for determining visibility conditions of an environment in which an autonomous vehicle is operated and performing driving related operations based on the visibility conditions. An example method of adjusting driving related operations of a vehicle includes determining, by a computer located in an autonomous vehicle, a visibility related condition of an environment in which the autonomous vehicle is operating, adjusting, based at least on the visibility related condition, a set of one or more values of one or more variables associated with a driving related operation of the autonomous vehicle, and causing the autonomous vehicle to be driven to a destination by causing the driving related operation of one or more devices located in the autonomous vehicle based on at least the set of one or more values.