Autonomous Vehicle Alert Calling for Passenger Emergency Response
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Solution Overview
Problem
There is a need for a method to efficiently operate an autonomous vehicle (AV) that can detect alert conditions and automatically initiate communication with passengers or external parties to address their needs or resolve incidents.
Innovation Solution
The method involves detecting alert conditions within the AV using data from its electronic sensor suite, and automatically initiating a call with another party to communicatively couple the passenger to the call, allowing them to communicate with the other party.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the AV system automatically initiates calls for all detected alert conditions, then passenger safety and response effectiveness are improved, but system complexity and false alarm risks increase
Solution Approach 1:
The system performs preliminary classification of alert conditions into severity levels (emergency, non-emergency, informational) before initiating communication. This preliminary action allows the system to prepare appropriate response protocols in advance, improving safety for true emergencies while avoiding unnecessary complexity for minor conditions.
Solution Approach 2:
Different communication protocols and response mechanisms are applied to different types of alert conditions. Emergency conditions trigger immediate automated calls to emergency services, while non-emergency conditions use different communication channels. This local differentiation improves reliability for critical situations without uniformly increasing system complexity across all scenarios.
2Measurement precision
If the AV uses multiple sensors to detect alert conditions, then detection accuracy and passenger safety are improved, but device complexity and cost increase
Solution Approach 1:
The sensor suite is segmented into functional groups (collision sensors, environmental sensors, passenger monitoring sensors, vehicle system sensors) that detect different types of alert conditions. This segmentation allows the system to achieve high detection accuracy for specific condition types while managing overall system complexity through modular architecture.
Solution Approach 2:
Multiple sensors are integrated into a unified alert condition detection system that processes diverse sensor inputs through a common evaluation framework. This multi-functional approach allows the same sensor suite to detect various types of alert conditions (collisions, environmental hazards, passenger emergencies) without requiring separate detection systems for each condition type.
3Loss of time
If the AV automatically initiates calls without human confirmation, then response time is improved, but risk of erroneous communication increases
Solution Approach 1:
The system performs preliminary validation of detected alert conditions against predefined criteria and thresholds before automatically initiating calls. This preliminary check ensures that only conditions meeting emergency criteria trigger automated communication, reducing erroneous calls while maintaining rapid response for true emergencies.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor sensor data and system state during the alert condition evaluation process. This feedback allows the system to confirm whether detected conditions warrant automated communication, improving communication accuracy while maintaining rapid response times through automated decision-making for confirmed emergencies.
Data Source
AI summary
There is disclosed a method of operating an autonomous vehicle (AV), including: detecting an alert condition within the AV via data from an electronic sensor suite of the AV; based at least in part on detecting the alert condition, automatically initiating a call with another party; and communicatively coupling a passenger of the AV to the conference call, whereby the passenger can communicate with the other party via the conference call.