Lane Path Modification for Autonomous Obstruction Avoidance
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Solution Overview
Problem
Autonomous vehicles face challenges in safely navigating environments without lane markings and adapting to dynamic changes such as obstructions, as existing systems lack effective methods to modify lane path descriptors in response to user input and real-time sensor data.
Innovation Solution
A system that generates and modifies lane path descriptors based on user input, allowing users to visualize and alter lane paths, and integrates this data into machine learning models for improved navigation, including the detection of road obstructions, enabling autonomous vehicles to safely traverse unmarked roadways and dynamic environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous vehicles use existing lane path descriptors for navigation, then they can traverse marked roadways, but they fail to navigate safely in environments without lane markings or with dynamic obstructions
Solution Approach 1:
The system dynamically modifies lane path descriptors in response to real-time sensor data and user input. Lane paths are not static but can be adjusted to account for obstructions, unmarked roadways, and changing environmental conditions. The modification system updates lane path descriptors to reflect current navigable areas, enabling safe traversal through dynamic environments.
Solution Approach 2:
The system incorporates feedback loops where sensor data from the environment is continuously processed, and lane path descriptors are modified based on this feedback. User input serves as additional feedback, allowing human operators to correct or refine automated lane path interpretations. This feedback mechanism ensures the navigation system adapts to actual road conditions rather than relying solely on pre-defined paths.
2Reliability
If the system modifies lane path descriptors based on user input, then navigation safety improves, but system complexity increases
Solution Approach 1:
The system introduces an intermediary modification layer between the raw sensor data and the navigation decision-making process. This intermediary system processes user input and sensor data to generate modified lane path descriptors, acting as a buffer that simplifies the overall system architecture. Rather than having users directly control navigation or the system operating autonomously without human input, the intermediary modification system integrates both inputs in a structured manner.
3Reliability
If lane path descriptors are altered to avoid obstructions, then vehicle safety improves, but the complexity of path planning increases
Solution Approach 1:
The path planning process is segmented into distinct stages: initial lane path descriptor generation, obstruction detection through sensor data processing, user input reception, lane path modification, and final navigation execution. This segmentation allows each component to focus on a specific task, reducing overall planning complexity. The modification of lane paths to avoid obstructions is handled as a separate, specialized function rather than being embedded in the entire path planning process.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that generates lane path descriptors for use by autonomous vehicles. One of the methods includes receiving data that defines valid lane paths in a scene in an environment. Each valid lane path represents a path through the scene that can be traversed by a vehicle. User interface presentation data can be provided to a user device. The user interface can contain: (i) a first display area that displays a first visual representation of the sensor measurement; and (ii) a second display area that displays a second visual representation of the set of valid lane paths. User input modifying the second visual representation of the set of valid lane paths can be received; and in response to receiving the user input, the set of valid lane paths of the scene in the environment can be modified.