Mixed-Autonomy Platoon Control Using Indirect Headway Guidance
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Solution Overview
Problem
Existing systems face inefficiencies in controlling mixed vehicle platoons that include both controlled and uncontrolled vehicles, as manually operated vehicles disrupt the platoon dynamics, leading to increased traffic congestion and challenges in enforcing uniform control methods.
Innovation Solution
A system utilizing a headway-based model and reinforcement learning to indirectly control uncontrolled vehicles by setting constraints on maximum headway and speed, allowing controlled vehicles to influence the behavior of uncontrolled vehicles through optimized performance metrics, thereby encouraging self-imposed control and maintaining platoon formation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If uniform control methods are enforced on all vehicles in the platoon, then control consistency is improved, but manually operated vehicles cannot comply leading to platoon disruption
Solution Approach 1:
The patent introduces an intermediary control approach where the central control system does not directly command uncontrolled vehicles, but instead sends control instructions to controlled vehicles which then indirectly influence uncontrolled vehicles through their motion behavior. This intermediary mechanism allows uniform control objectives to be achieved while accommodating the limitations of manually operated vehicles.
Solution Approach 2:
The patent enables uncontrolled vehicles to self-regulate their motion based on the behavior of controlled vehicles in the platoon. By observing the speed and position adjustments of controlled vehicles, uncontrolled vehicles naturally adapt their own motion to maintain platoon formation, achieving self-imposed control without direct intervention.
2Productivity
If manually operated vehicles are allowed in the platoon, then traffic flow flexibility is improved, but platoon control efficiency deteriorates
Solution Approach 1:
The central control system acts as an intermediary that coordinates between controlled and uncontrolled vehicles, using controlled vehicles as mediators to indirectly guide the behavior of uncontrolled vehicles, thereby maintaining overall platoon control reliability while allowing manual vehicle participation.
Solution Approach 2:
The patent dynamically adjusts control parameters such as headway distance and speed references for controlled vehicles based on the presence and behavior of uncontrolled vehicles. This parameter adaptation allows the platoon to maintain stability and control reliability while accommodating the variable nature of manually operated vehicles.
3Reliability
If controlled vehicles maintain larger headway for safety, then collision risk is reduced, but aerodynamic drag increases reducing energy efficiency
Solution Approach 1:
The patent implements dynamic headway adjustment where controlled vehicles continuously adapt their following distance based on real-time conditions including the presence of uncontrolled vehicles, traffic density, and speed variations. This dynamic approach allows the platoon to maintain safety margins while minimizing headway to preserve aerodynamic efficiency and reduce energy consumption.
Solution Approach 2:
The control system dynamically changes the headway parameter based on operational conditions, adjusting it to optimal values that balance safety requirements with energy efficiency goals. During stable platoon operation, smaller headways are maintained for drag reduction, while safety margins are increased when detecting potential risks or presence of uncontrolled vehicles.
Data Source
AI summary
A system for direct and indirect control of mixed-autonomy vehicles receives a traffic state of a group of mixed-autonomy vehicles traveling in the same direction, wherein the group of mixed-autonomy vehicles includes controlled vehicles willing to participate in a platoon formation and at least one uncontrolled vehicle, and wherein the traffic state is indicative of a state of each vehicle in the group, submit the traffic state into a parameterized function trained to transform the traffic state into target headways for the mixed-autonomy vehicles to produce the target headways, and submit the target headways to a headway-based model configured to map the target headways to target speeds of the mixed-autonomy vehicles to produce the target speeds. The system determines and transmits control commands to the controlled vehicle based on one or combination of the target headways and the target speeds.