Autonomous Pickup Path Safety Scoring for Passenger Transfer
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Solution Overview
Problem
Autonomous vehicles face challenges in safely executing passenger pickup and delivery due to unpredictable environments that deviate from normal roadway navigation, posing safety risks to passengers.
Innovation Solution
The vehicle determines a safety confidence score using machine-learned models and sensor data to assess the safety of the pickup or delivery path, and if unsafe, it overrides the planning component to execute mitigation actions such as altering the trajectory, halting operations, or recalculating the endpoint to ensure passenger safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the autonomous vehicle stops at unusual places in the roadway for passenger pickup/delivery, then the vehicle can serve more locations and improve accessibility, but passenger safety is compromised due to lack of roadway marker guidance and unpredictable environments
Solution Approach 1:
The system performs preliminary safety assessment by determining a safety confidence score before executing the pickup or delivery operation. This advance evaluation allows the vehicle to identify potential safety issues and take preventive actions, such as selecting alternative locations or adjusting operational parameters, before the actual passenger transfer occurs.
Solution Approach 2:
The system continuously monitors the environment using sensor data and updates the safety confidence score in real-time. This feedback mechanism allows the vehicle to respond to changing conditions during the approach to and execution of the pickup/delivery operation, dynamically adjusting its behavior to maintain safety while achieving operational flexibility.
2Reliability
If the vehicle uses machine-learned models and sensor data to determine safety confidence scores, then passenger safety is improved through proactive identification of unsafe conditions, but the system complexity increases
Solution Approach 1:
The safety confidence score determination system serves multiple functions: it evaluates environmental safety, monitors object trajectories, assesses passenger paths, and guides operational decisions. This multi-functional approach consolidates what could be separate complex subsystems into a unified safety assessment mechanism, reducing overall system complexity while maintaining comprehensive safety coverage.
Solution Approach 2:
The system uses its own sensor data and machine-learned models to autonomously determine safety confidence scores without requiring external intervention or complex centralized control. The autonomous vehicle performs its own safety assessment, making the system self-sufficient and reducing the need for additional complex infrastructure or external monitoring systems.
3Reliability
If the vehicle alters operation based on safety confidence score thresholds, then passenger safety is enhanced through mitigation actions, but the operational efficiency and productivity decrease
Solution Approach 1:
The system applies mitigation actions selectively based on the safety confidence score. When the score is above the threshold, normal operations proceed without interruption. When the score falls below the threshold, only specific mitigation actions are applied to address the identified safety concerns. This partial action approach ensures safety is maintained when needed while minimizing disruptions to operational efficiency during safe conditions.
Solution Approach 2:
The safety confidence score is determined periodically and at key decision points during the pickup/delivery operation. This periodic assessment allows the vehicle to maintain normal efficient operation between safety checks while still providing continuous safety monitoring. The systematic timing of safety evaluations ensures that productivity is not continuously compromised by constant safety interventions.
Data Source
AI summary
A passenger may be rather vulnerable to safety risks during pickup and/or drop-off of a passenger by a vehicle. To mitigate or eliminate such risk, the vehicle may determine an endpoint for a vehicle route to pickup or drop-off a passenger at a location. The vehicle may determine an estimated path between the endpoint and the location and may determine a safety confidence score by a machine-learned model for the estimated path and/or may predict a trajectory of a detected object to ascertain whether the estimated path is safe. The vehicle may execute any of a number of different mitigation actions to reduce or eliminate a safety risk if one is detected.