Autonomous Vehicle Queue Detection for Pickup and Drop-Off Control
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Solution Overview
Problem
Autonomous vehicles lack the intuition to recognize and respond to queuing behaviors, often causing inconvenience or annoyance to passengers and other road users by improperly joining or exiting queues.
Innovation Solution
The vehicle's computing devices determine if a queue exists at a pickup or drop-off location using sensor data and map information, and then decide whether to join the queue to avoid inconveniencing other road users, controlling the vehicle to move along the queue and reach a designated spot for pickup or drop-off.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous vehicles operate in fully autonomous mode without human drivers, then automation level is improved, but ability to recognize and respond to queuing behaviors deteriorates
Solution Approach 1:
The autonomous vehicle uses sensor data to continuously monitor traffic patterns and detect queues in real-time, creating a feedback loop that allows the vehicle to adapt its behavior based on observed conditions. The system processes sensor inputs, determines queue presence, and adjusts vehicle actions accordingly, enabling autonomous vehicles to respond to dynamic traffic situations without human intervention.
Solution Approach 2:
The autonomous vehicle independently determines whether to join a queue by analyzing sensor data and traffic patterns without requiring human driver input. The system autonomously makes decisions about queue joining, exits, and maneuvers based on its own sensor observations and programmed logic, demonstrating self-service capability in complex social driving scenarios.
2Productivity
If autonomous vehicles join queues without proper detection, then productivity is improved by reducing wait times, but harmful factors increase by inconveniencing other road users
Solution Approach 1:
The autonomous vehicle performs preliminary detection of queue conditions using sensor data before making the decision to join or exit a queue. By proactively identifying queue presence and characteristics in advance, the system can plan appropriate maneuvers that improve efficiency while minimizing disruption to other road users, rather than reacting impulsively to traffic conditions.
3Measurement precision
If autonomous vehicles use sensor data to detect queues, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The autonomous vehicle uses its existing sensor suite (cameras, LIDAR, radar) for multiple purposes including queue detection, general obstacle avoidance, and traffic monitoring. By making the sensor system multi-functional, the vehicle achieves precise queue detection without adding dedicated specialized hardware, thereby improving measurement precision while limiting the increase in device complexity.
Data Source
AI summary
Aspects of the disclosure provide for controlling an autonomous vehicle to respond to queuing behaviors at pickup or drop-off locations. As an example, a request to pick up or drop off a passenger at a location may be received. The location may be determined to likely have a queue for picking up and dropping off passengers. Based on sensor data received from a perception system, whether a queue exists at the location may be determined. Once it is determined that a queue exists, it may be determined whether to join the queue to avoid inconveniencing other road users. Based on the determination to join the queue, the vehicle may be controlled to join the queue.