Anomaly Management for Diverse Driver Capabilities
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Solution Overview
Problem
In a roadway environment, the challenge lies in managing anomalies caused by drivers with different capabilities, where tentative and inexperienced drivers interact with experienced drivers, leading to concerns and indecision, and existing systems struggle to identify and mitigate these anomalies effectively.
Innovation Solution
A system comprising one or more computers configured to determine ego and remote vehicle behaviors, calculate variances, and generate a driving management plan to mitigate anomalies by executing machine learning or time series analysis algorithms, and implementing this plan to ensure compatibility with the ego driver's capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If drivers with different capabilities (experienced and inexperienced) drive proximate to each other, then roadway diversity and real-world driving scenarios are represented, but safety concerns and indecision arise due to incompatible driving behaviors
Solution Approach 1:
The system introduces an intermediary anomaly management layer that mediates interactions between drivers with different capabilities. This layer detects behavioral incompatibilities and generates management plans that coordinate actions between ego and remote vehicles, allowing diverse driving styles to coexist safely without direct conflict.
Solution Approach 2:
The system dynamically changes driving parameters (speed, lane position, following distance) based on detected anomalies in remote vehicle behavior. When incompatible driving patterns are identified, the ego vehicle adjusts its parameters to mitigate conflict and maintain safety while still operating in diverse roadway environments.
2Reliability
If the system monitors and analyzes driver behavior to identify anomalies, then driving safety can be improved, but system complexity increases due to behavior analysis requirements
Solution Approach 1:
The system performs self-service by automatically detecting anomalies in remote vehicle behavior and generating appropriate management plans without requiring complex external intervention. The anomaly management client autonomously analyzes behavior data, identifies incompatibilities, and executes mitigation strategies, reducing the need for additional system components.
Solution Approach 2:
The system uses multi-functional behavior data that serves multiple purposes: it characterizes driver capabilities, detects anomalies, generates management plans, and evaluates their effectiveness. This universal use of behavior data reduces the need for separate specialized systems for each function.
3Reliability
If the system generates and implements driving management plans to mitigate anomalies, then safety is enhanced, but response time may be reduced due to plan generation and execution steps
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and characterizing remote vehicle behaviors in advance. When an anomaly is detected, the management plan can be generated more quickly because the system already has pre-established behavior models and capability assessments, reducing the time needed for analysis and response.
Data Source
AI summary
The disclosure includes embodiments for managing vehicles under anomalous driving behavior. In some embodiments, a method includes determining, by the processor, an ego behavior associated with the ego vehicle and a remote behavior associated with a remote vehicle. The method includes calculating a variance between the ego behavior and the remote behavior. The method includes determining a presence of an anomaly based on the variance satisfying a threshold, wherein the satisfying the threshold indicates the ego behavior is incompatible with the remote behavior. The method includes generating a driving management plan which is configured to mitigate the anomaly and is consistent with the ego behavior. The method includes implementing the driving management plan so that the threshold is no longer satisfied.