Autonomous Vehicle Fleet Control for Anomaly Neutralization
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Solution Overview
Problem
Human-driven vehicles can negatively impact traffic efficiency and safety due to abnormal actions such as excessive speed, sudden lane changes, and braking, which autonomous vehicles may struggle to counteract effectively.
Innovation Solution
A traffic control system utilizing reinforcement-learning algorithms to identify anomaly vehicles and direct controlled vehicles to neutralize these negative impacts by executing actions such as speed control, lane blocking, or surrounding the anomaly vehicles, thereby improving overall traffic flow and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles communicate and work in concert to reduce traffic congestion, then traffic efficiency is improved, but the effectiveness is reduced when human-operated anomaly vehicles perform abnormal actions such as excessive speed, sudden lane changes, and braking
Solution Approach 1:
The patent introduces controlled vehicles as intermediary agents between the autonomous vehicle network and anomaly vehicles. These controlled vehicles actively intervene to neutralize the harmful effects of anomaly vehicles, thereby protecting the overall traffic system from disruptions caused by human-operated vehicles performing abnormal actions.
Solution Approach 2:
The system employs controlled vehicles to perform preliminary counter-actions against potential harmful behaviors of anomaly vehicles. By detecting anomaly patterns and deploying controlled vehicles in advance to neutralize these threats, the system prevents abnormal actions from significantly impacting traffic efficiency before they can cause widespread disruption.
2Reliability
If controlled vehicles are deployed to neutralize anomaly vehicles through actions such as speed control, lane blocking, and surrounding, then traffic safety and flow are improved, but the complexity of the traffic control system increases
Solution Approach 1:
The controlled vehicles are equipped with autonomous capabilities to independently detect anomaly vehicles, determine appropriate neutralization strategies, and execute control actions without requiring constant external coordination. This self-service approach reduces the operational complexity of the overall traffic control system while maintaining high safety standards.
Solution Approach 2:
The system employs dynamic control strategies where controlled vehicles adapt their behavior based on real-time conditions and the specific actions of anomaly vehicles. Rather than following rigid protocols, the controlled vehicles can adjust their speed, positioning, and intervention intensity dynamically, which simplifies the control architecture while achieving reliable safety outcomes.
Data Source
AI summary
A system and method for controlling one or more vehicles with one or more controlled vehicles may include one or more processors and a memory in communication with the one or more processors. The memory may include one or more modules that cause the one or more modules to obtain a state of an environment having a universe of vehicles operating therein, identify one or more anomaly vehicles from the universe of vehicles operating in the environment, select one more actions to control a plurality of controlled vehicles to control the operation of one or more anomaly vehicles and direct the plurality of controlled vehicles execute the one or more actions. The selecting of one or more actions may be performed by utilizing a reinforcement-learning trained algorithm.