Autonomous Vehicle Profile Building via Proactive Maneuvers
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Solution Overview
Problem
Autonomous vehicles face challenges in building accurate vehicle profiles for rare driving situations due to limited data availability, particularly for interactions that occur infrequently in real-life scenarios.
Innovation Solution
The vehicle is equipped with an object detection system and autonomous control system that performs specific driving maneuvers to interact with surrounding vehicles, collecting data to build or update vehicle profiles based on attributes such as manufacturer, body style, and driving patterns, and predicts future behavior of surrounding vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the autonomous vehicle collects data from real-world interactions to build vehicle profiles, then the accuracy and completeness of vehicle profiles improve, but the availability of data for rare driving situations remains insufficient
Solution Approach 1:
The autonomous vehicle proactively creates driving scenarios by performing specific maneuvers (such as merging, lane changes, or braking) to elicit reactions from surrounding vehicles. This preliminary action generates interaction data for rare driving situations that would otherwise not occur naturally, enabling the building of comprehensive vehicle profiles even for infrequent events.
2Loss of information
If the autonomous vehicle performs driving maneuvers to create reactions from surrounding vehicles, then data collection for building vehicle profiles improves, but the complexity of vehicle control systems increases
Solution Approach 1:
The autonomous control system monitors reactions from surrounding vehicles in real-time and uses this feedback to adjust subsequent driving maneuvers. The system iteratively refines its approach by analyzing whether the created reactions provide useful data for vehicle profiling, thereby managing control complexity through adaptive feedback loops rather than predetermined complex sequences.
3Reliability
If the autonomous vehicle builds detailed vehicle profiles for all surrounding vehicles, then the ability to predict future behavior improves, but the computational resources and processing time increase
Solution Approach 1:
The system applies different levels of profiling detail to different surrounding vehicles based on their relevance to the autonomous vehicle's current context. Instead of uniformly detailed profiles for all vehicles, the system focuses computational resources on profiling vehicles that pose potential risks or are involved in rare driving situations, thereby reducing overall processing time while maintaining prediction accuracy for critical scenarios.
Data Source
AI summary
Vehicle systems and methods for autonomously controlling a vehicle to create a reaction by one or more surrounding vehicles, where the reaction is used to build one or more vehicle profiles are disclosed. In one embodiment, a vehicle includes an object detection system configured to output an object signal in response to detecting one or more vehicles operating in an environment surrounding the vehicle, an autonomous control system configured to autonomously control one or more vehicle systems of the vehicle, one or more processors, and one or more non-transitory memory modules communicatively coupled to the processors and storing machine-readable instructions that, when executed, cause the one or more processors to perform at least determining the vehicle is operating in an autonomous driving mode, and in response to determining the vehicle is operating in the autonomous driving mode, determine a presence of the one or more vehicles.