Swarm Vehicle Invitation Using Social Alignment and Disruption Values
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Solution Overview
Problem
Autonomous vehicles face challenges in interacting with human drivers and other vehicles due to differing altruistic and egotistic behaviors, which can create traffic bottlenecks and affect overall traffic flow.
Innovation Solution
A system and method for swarm invitation based on social values, where a processor calculates a total disruption value and social alignment value of proximate vehicles to determine if they align with a desired social alignment value of a swarm, sending a swarm request to vehicles exhibiting altruistic behavior to join the swarm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles exhibit altruistic behavior to benefit other road users, then social alignment value improves, but traffic flow efficiency deteriorates due to bottlenecks at intersections
Solution Approach 1:
The system dynamically adjusts the autonomous vehicle's behavior based on real-time conditions. The processor calculates disruption values and social alignment values continuously, allowing the vehicle to switch between altruistic and egotistic behaviors as needed. This dynamic adaptation resolves the contradiction by making behavior flexible rather than fixed, enabling the vehicle to be altruistic when appropriate and efficient when needed.
Solution Approach 2:
The system changes the behavioral parameters of the autonomous vehicle based on calculated values. By monitoring disruption values (velocity and position) and comparing them against threshold values, the system adjusts the vehicle's social alignment parameter in real-time. This allows the vehicle to optimize between social benefit and traffic efficiency by changing its behavioral parameters dynamically.
2Productivity
If autonomous vehicles exhibit egotistical behavior to optimize their own decisions, then individual vehicle performance improves, but overall traffic flow deteriorates
Solution Approach 1:
The system uses feedback from the environment to adjust individual vehicle decisions. The processor continuously monitors the autonomous vehicle's position and velocity disruption values, compares them to threshold values, and adjusts behavior accordingly. This feedback mechanism ensures that individual vehicle optimization does not negatively impact overall traffic flow, as the system learns from the consequences of its decisions.
3Reliability
If the swarm calculates disruption values and sends swarm requests to align social values, then swarm efficacy improves, but system complexity increases
Solution Approach 1:
The system enables vehicles to self-evaluate their social alignment with the swarm based on calculated disruption values. Each vehicle independently determines its own social alignment value by comparing its disruption values to threshold values, and autonomously decides whether to join or remain in the swarm. This self-service approach improves swarm efficacy while minimizing the need for complex centralized control.
Data Source
AI summary
Systems and methods for swarm invitation based on social values are provided. In one embodiment, a method includes calculating a total disruption value of a proximate vehicle on a roadway with a plurality of swarm vehicles of a swarm on the roadway. The total disruption value of the proximate vehicle is based on a velocity disruption value of the proximate vehicle and a position disruption value of the proximate vehicle. The method also includes determining a proximate social alignment value of the proximate vehicle based on a comparison of the total disruption value to a threshold disruption value. The threshold disruption value is based on a desired social alignment value of the swarm. The method yet further includes sending a swarm request to the proximate vehicle when the proximate social alignment value corresponding to the desired social alignment value.