Autonomous Vehicle Path Adjustment for Target Zone Maneuvers

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Autonomous vehicles face challenges in efficiently planning paths that account for specific actions such as picking up or dropping off passengers or items, as existing systems often rely on nominal paths that do not consider obstacles or dynamic environments.

Innovation Solution

A computer-implemented method that accesses map data and sensor data to alter nominal paths, designating action regions for target zones, generating longitudinal plans, and determining target velocities to ensure safe and efficient execution of actions like turns or pick-ups/drop-offs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If autonomous vehicles use nominal paths for navigation, then the path planning is simple and fast, but the vehicle cannot account for obstacles or dynamic environments requiring specific actions

Engineering Contradiction:

Improveability to account for obstacles and dynamic environmentsVSAvoidpath planning complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The path planning is divided into two segments: a nominal path segment for simple navigation and an altered path segment for handling target zones with specific actions. The system segments the driving task into routine navigation (using nominal paths) and special actions (using altered paths), allowing complexity to be applied only where needed rather than throughout the entire path planning process.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system pre-identifies target zones and determines altered paths in advance before actual navigation. By performing path alteration planning beforehand and pre-defining action regions, the system prepares alternative paths for known target zones, reducing real-time computational complexity while maintaining adaptability to dynamic environments.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If autonomous vehicles alter nominal paths to traverse target zones, then the vehicle can perform specific actions safely, but the processing cycles and energy consumption increase

Engineering Contradiction:

Improvesafety of action executionVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system applies path alteration only locally within target zones rather than throughout the entire route. By designating specific action regions where altered paths are needed and maintaining nominal paths elsewhere, the system ensures safety for critical actions while minimizing the computational energy required for path planning.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system performs partial path alteration only for portions of the route that require specific actions, rather than altering the entire path. This selective approach applies computational resources only where necessary, reducing overall energy consumption while maintaining the reliability needed for safe action execution in target zones.

Inventive Principle:

Principle #16Partial or excessive action

3Productivity

If autonomous vehicles use detailed path planning for all regions, then the vehicle can handle dynamic environments, but the processing cycles increase reducing efficiency

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidprocessing time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system segments the geographic area into target zones requiring detailed planning and non-target zones using nominal paths. This segmentation allows the vehicle to use computationally intensive detailed planning only where necessary (in target zones) while using efficient nominal paths elsewhere, improving overall processing efficiency without sacrificing safety in critical regions.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs detailed path planning in advance for target zones before navigation begins. By pre-computing altered paths for known target zones, the system reduces real-time processing requirements during actual navigation, thereby improving processing efficiency and reducing time loss during critical action execution.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12049238B2Systems and methods for autonomous vehicle motion control and motion path adjustments

Publication Date: 2024.07.30 AURORA OPERATIONS INC

AI summary

The present disclosure is directed to altering vehicle paths. In particular, a computing system can access map data for a geographic area. The computing system can obtain target zone data describing a target zone within the geographic area. The computing system can determine an altered nominal path to traverse the target zone. The computing system can designate a portion of the altered nominal path as a designated action region associated with the target zone. The computing system can generate a longitudinal plan for an autonomous vehicle through the geographic area based on the altered nominal path. The computing system can generate a target velocity for one or more portions of the nominal path within the designated action region. The computing system can generate a trajectory for the autonomous vehicle based on the target velocity and the altered nominal path.