Reverse Maneuver Prediction for Autonomous Vehicle Planning
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Solution Overview
Problem
Autonomous vehicles face challenges in predicting and accommodating the reverse maneuvers of other vehicles, particularly due to occluded or non-functional reverse lights, which can lead to inaccurate determinations and increased processing resources, affecting safety and efficiency.
Innovation Solution
The system uses sensor data, including image and environmental features, to determine the likelihood of a vehicle being in a reverse state through machine-learned models, allowing for the prediction of trajectories and control adjustments to safely and efficiently navigate around vehicles executing reverse maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If the system relies on reverse lights to determine vehicle reverse state, then detection is simplified, but detection accuracy deteriorates due to occluded or non-functional reverse lights
Solution Approach 1:
The patent introduces multiple intermediary indicators beyond reverse lights to detect vehicle reverse state. These include analyzing the vehicle's trajectory (whether it is moving backward), detecting reverse gear engagement status, and examining positioning data. By using these intermediary signals, the system compensates for failed reverse lights and maintains high detection accuracy.
Solution Approach 2:
The system employs a multi-functional detection approach where a single reverse state determination mechanism serves multiple purposes. The same sensor suite used for general navigation and obstacle detection is also utilized to detect reverse state through alternative indicators like trajectory analysis and gear status, making the detection system universal rather than specialized for reverse lights alone.
2Measurement precision
If the system uses multiple indicators to determine reverse state, then detection accuracy improves, but processing resources increase
Solution Approach 1:
The system performs preliminary filtering and prioritization of detection indicators. Instead of continuously processing all possible indicators with equal intensity, it pre-identifies the most reliable indicators for each situation (e.g., trajectory analysis when reverse lights are occluded, gear status when available) and processes those first. This preliminary action reduces unnecessary processing of less relevant indicators, conserving computational resources while maintaining accuracy.
Solution Approach 2:
The detection system dynamically adjusts which indicators are processed based on current conditions. When reverse lights are clearly visible and functional, the system relies primarily on that simple indicator. When reverse lights are occluded or non-functional, the system dynamically shifts to process alternative indicators like trajectory and gear status. This dynamic adaptation optimizes processing resource usage according to actual detection needs.
3Use of energy by moving object
If the system detects reverse maneuvers later, then processing load is reduced, but safety deteriorates due to increased collision risks
Solution Approach 1:
The system performs preliminary detection of reverse state using multiple indicators simultaneously rather than waiting for confirmation from a single source. By proactively identifying potential reverse maneuvers early through alternative indicators like trajectory changes or gear engagement, the system provides earlier warning to the autonomous vehicle, improving safety without requiring excessive processing load during critical moments.
Data Source
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AI summary
Techniques for determining that a first vehicle is associated with a reverse state, and controlling a second vehicle based on the reverse state, are described herein. In some examples, the first vehicle may provide an indication that the first vehicle will be executing a reverse maneuver, such as with reverse lights on the vehicle or by positioning at an angle relative to a road or parking space to allow for the reverse maneuver into a desired location. A planning system of the second vehicle (such as an autonomous vehicle) may receive sensor data and determine a variety of these indications to determine a probability that the vehicle is going to execute a reverse maneuver. The second vehicle can further determine a likely trajectory of the reverse maneuver and can provide appropriate accommodations (e.g., time and/or space) to allow the second vehicle to execute the maneuver safely and efficiently.