Autonomous Vehicle Emergency Detection With Remote Operator Guidance
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Solution Overview
Problem
Emergency vehicles' sirens can be difficult for autonomous vehicles to detect, especially when not in close proximity, posing challenges in training autonomous vehicles to interact appropriately with emergency services vehicles.
Innovation Solution
Implementing sensors on autonomous vehicles to detect light intensity, using machine learning to identify emergency services vehicles, and transmitting notifications and video feeds to remote operators for decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors detect light intensity and use machine learning to identify emergency vehicles, then the detection capability is improved, but the device complexity increases
Solution Approach 1:
The patent introduces a remote terminal as an intermediary between the autonomous vehicle and the operator. The vehicle's sensors and machine learning system detect emergency vehicles and transmit data to the remote terminal, which then relays information to the operator for final decision-making. This distributes system complexity across multiple components rather than concentrating it all in the vehicle itself.
Solution Approach 2:
The patent replaces traditional acoustic detection (sirens) with optical detection (light intensity sensors) and machine learning algorithms. This substitution enables detection at greater distances and in conditions where sirens are ineffective, improving detection capability while managing complexity through software-based solutions.
2Reliability
If the autonomous vehicle transmits video feed and notification to remote terminal, then the interaction reliability is improved, but the loss of time increases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring for emergency vehicles and maintaining ready-to-transmit communication channels. When an emergency vehicle is detected, the notification and video feed transmission is immediately initiated, reducing the effective response time despite the additional communication steps.
Solution Approach 2:
The patent establishes a feedback loop where the remote operator receives real-time video feeds and notifications, then provides commands back to the autonomous vehicle. This continuous feedback enables reliable interaction while minimizing time loss through immediate information exchange and rapid decision-making cycles.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables effective interaction with emergency services vehicles by allowing remote operators to guide autonomous vehicles to pull over or continue driving based on real-time video feeds, enhancing safety and responsiveness.
Implementation Method 1
sensors on the autonomous vehicle (referred to herein as an ego vehicle) can detect light intensity from an environment surrounding the autonomous vehicle
Data Source
AI summary
Provided are systems and methods for detecting an emergency services vehicle and controlling an autonomous vehicle to interact with the emergency services vehicle and emergency services personnel. In one example, a method may include storing sensor data captured of an environment surrounding the vehicle while the vehicle is on a road, determining whether an emergency services vehicle is present in the surrounding environment based on the sensor data, and in response to determining that the emergency vehicle is present in the surrounding environment, generating an alert and transmitting the alert to a user interface.