Driver Behavior Detection System for Autonomous Vehicle Communication
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Solution Overview
Problem
Interactions between autonomous vehicles and human-driven vehicles at intersections are hindered due to diminished communication, leading to potential safety issues and erratic behavior when human drivers intentionally manipulate rules to confuse autonomous vehicles.
Innovation Solution
Systems and methods that capture images of drivers and their surroundings to determine driving behavior, providing incentives based on thresholds, allowing for improved communication and decision-making between human and autonomous vehicles through visual or wireless communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous vehicles use sensor and image processing technologies to detect the world around them, then they can operate autonomously, but communication with human-driven vehicles is diminished leading to standstills and safety issues at intersections
Solution Approach 1:
The patent introduces visual indicators (LED lights) as an intermediary communication medium between autonomous vehicles and human-driven vehicles. These indicators convey the autonomous vehicle's detected driver behavior and intended actions, bridging the communication gap caused by lack of human interaction cues.
Solution Approach 2:
The patent uses color changes in visual indicators (e.g., green LED for yield, red LED for proceed) to communicate the autonomous vehicle's interpreted driver behavior and right-of-way status. This allows human drivers to quickly understand the autonomous vehicle's intentions without complex sensor data exchange.
2Reliability
If autonomous vehicles follow traffic rules strictly, then they operate predictably, but human drivers may manipulate rules to cause erratic autonomous vehicle behavior
Solution Approach 1:
The patent implements preliminary detection and verification of driver behavior patterns before the autonomous vehicle responds. By capturing images, analyzing driver actions, and confirming behavior patterns in advance, the system prevents reactive erratic behavior while maintaining rule-following predictability.
Solution Approach 2:
The patent establishes a feedback loop where the autonomous vehicle communicates its interpreted driver behavior and intended actions through visual indicators. This feedback allows human drivers to understand the autonomous vehicle's response to their actions, reducing manipulation attempts and improving mutual predictability.
3Loss of information
If human drivers gesture to indicate yielding or expecting right of way, then communication between drivers is enhanced, but autonomous vehicles cannot interpret these gestures leading to confusion
Solution Approach 1:
The patent replaces complex gesture recognition mechanisms with simpler image capture and analysis. Instead of requiring sophisticated mechanical or sensor-based gesture detection, the system uses cameras to capture driver images and software to analyze gestures, making the detection process more reliable and easier to implement.
4Reliability
If both vehicles stop at an intersection to figure out right of way, then safety is maintained, but productivity and traffic flow are reduced
Solution Approach 1:
The patent implements preliminary communication of driver behavior and intended actions through visual indicators before vehicles reach the intersection. This allows both vehicles to understand each other's intentions in advance, eliminating the need to stop and figure out right of way, thus maintaining safety while improving traffic flow.
Data Source
AI summary
Embodiments are directed towards the interpretation of driver behavior and communication with autonomous vehicles and incentivizing drivers based on the driver's behavior. A computing device that sits on the dashboard of a vehicle includes at least one camera and circuitry. The computing device captures first images of the driver in the vehicle and second images of an area outside the vehicle. The computing device identifies another vehicle based on an analysis of the second images. The computing device determines a driving behavior of the driver based on an analysis of the first images. The computing device determines if the driving behavior satisfies a positive incentive threshold or a negative incentive threshold. The computing device selects and provides a positive or negative incentive to the driver in response to the driving behavior satisfying the positive incentive threshold or the negative incentive threshold, respectively.


