Cooperative Maneuvering System for Connected Vehicle Congestion
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Solution Overview
Problem
Current systems for managing cooperative maneuvering among connected vehicles lack effective methods to prevent congestion and traffic instability during complex maneuvers like lane changes and merges, as existing standards do not adequately address the number of vehicles involved and specific maneuver details.
Innovation Solution
A method and system that determine the appropriate maneuver for an ego vehicle based on traffic information, select cooperative vehicles, simulate the maneuver's impact on congestion, and adjust the number of vehicles involved to prevent congestion, using processors and sensors to communicate and coordinate with other vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If more cooperative vehicles are selected to perform coordinated maneuvers, then the maneuver efficiency and traffic flow improvement increase, but the risk of triggering congestion and traffic instability increases
Solution Approach 1:
The system performs simulation of the cooperative maneuver before actual execution to predict potential congestion and traffic instability. This preliminary action allows the system to identify problematic scenarios and adjust the maneuver plan accordingly, preventing harmful effects before they occur in the actual traffic flow
Solution Approach 2:
The system uses simulation results as feedback to iteratively adjust the maneuver parameters and cooperative vehicle selection. The simulation provides information about potential congestion and instability, which is fed back into the decision-making process to optimize the maneuver plan and avoid triggering harmful traffic effects
2Ease of operation
If the number of cooperative vehicles involved in the maneuver is increased, then the maneuver can be performed more smoothly, but the complexity of coordinating and managing these vehicles increases
Solution Approach 1:
The system introduces a centralized coordination mechanism that acts as an intermediary to manage the cooperative maneuver. This mediator collects information from all cooperative vehicles, performs simulation-based optimization, and distributes coordinated instructions, thereby managing the complexity of multi-vehicle coordination without requiring direct peer-to-peer communication between all vehicles
3Stability of the object's composition
If detailed simulation and adjustment processes are implemented to prevent congestion, then traffic stability is improved, but the computation time and processing requirements increase
Solution Approach 1:
The system performs simulation and adjustment processes selectively based on the maneuver context and traffic conditions. Rather than always performing full simulations, the system applies simulation and adjustment only when necessary to prevent congestion, thereby reducing overall computation time while maintaining traffic stability when needed
Data Source
AI summary
A method for determining a cooperative maneuver for an ego vehicle is provided. The method includes determining a maneuver of the ego vehicle based on traffic information in a target lane, selecting one or more cooperative vehicles to be involved in the maneuver, determining whether the maneuver of the ego vehicle and actions of the one or more cooperative vehicles trigger congestion in the target lane based on simulation of the maneuver and the actions, instructing the ego vehicle to perform the maneuver in response to determining that the maneuver of the ego vehicle and actions of the one or more cooperative vehicles do not trigger congestion, and adjusting a number of cooperative vehicles to be involved in the maneuver in response to determining that the maneuver of the ego vehicle and actions of the one or more cooperative vehicles trigger congestion.