Autonomous Vehicle Waypoint Queueing for Low-Connectivity Pickup Control
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Solution Overview
Problem
Autonomous vehicles face challenges in seamlessly managing passenger pick-up and drop-off operations, especially in areas with high latency or low connectivity, and require improved systems to handle changing passenger interactions and road conditions.
Innovation Solution
An integrated on-vehicle queue management system that communicates with a virtual driver system to manage passenger waypoints, allowing for uninterrupted operations by storing information locally and adjusting queues based on real-time passenger presence and changing conditions, such as traffic or new passenger pickups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle relies on cloud servers for waypoint management, then centralized control and coordination can be achieved, but operations are interrupted in areas with high latency or low connectivity
Solution Approach 1:
The system performs preliminary actions by downloading and storing waypoint queue data locally in the vehicle's integrated on-vehicle system before connectivity is lost. This local storage enables the vehicle to continue operating autonomously without real-time cloud server communication, resolving the contradiction between centralized control and operational continuity in low-connectivity areas
Solution Approach 2:
The waypoint management system is segmented into two independent components: cloud server-based centralized control for data generation and update, and local on-vehicle queue management for execution. This segmentation allows the vehicle to operate independently when disconnected, while still benefiting from centralized coordination when connected, thus maintaining reliability without sacrificing data availability
2Productivity
If the vehicle adjusts the waypoint queue based on real-time conditions, then operational efficiency is improved, but system complexity increases
Solution Approach 1:
The waypoint queue is implemented as a dynamic data structure that automatically adjusts its contents based on real-time sensor data, passenger presence detection, and traffic conditions. The queue management system dynamically adds, removes, or reorders waypoints without requiring complex manual intervention, improving productivity while keeping the system architecture relatively simple through automated adaptive behavior
Solution Approach 2:
The system incorporates feedback mechanisms where sensor data about passenger presence, vehicle occupancy, and road conditions continuously informs queue adjustments. This feedback loop enables the system to automatically optimize its waypoint sequence based on actual operating conditions, achieving high productivity through simple rule-based responses to sensed conditions rather than complex decision-making architecture
Data Source
AI summary
An autonomous vehicle comprising an integrated on-vehicle system having a queue management system configured to manage a queue of passenger waypoints, wherein the integrated on-vehicle system is configured to assign the passenger waypoints to a virtual driver system (VDS) of the autonomous vehicle.