Autonomous Vehicle Queueing Control at Pickup and Drop-Off Zones
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Solution Overview
Problem
Autonomous vehicles lack the intuition to recognize and respond to queuing behaviors, leading to potential inconvenience or annoyance to passengers and other road users, and may cause traffic congestion or unsafe conditions.
Innovation Solution
The vehicle's computing devices determine the likelihood of a queue at a location using sensor data and map information, assess whether to join the queue, and control the vehicle's movements to minimize inconvenience, using trained models to identify designated loading spots and predict wait times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous vehicles operate without human drivers, then automation level increases, but ability to recognize and respond to queuing behaviors deteriorates
Solution Approach 1:
The autonomous vehicle uses its own sensor data and processing capabilities to independently detect queues, determine whether to join them, and execute queuing maneuvers without human intervention or external assistance, achieving self-service in social situation recognition and response
Solution Approach 2:
The vehicle continuously monitors sensor data to detect queue formations, processes this information through trained models, and adjusts its driving behavior accordingly, creating a closed-loop feedback system that enables adaptive response to dynamic queuing conditions
2Productivity
If autonomous vehicles do not join queues, then traffic flow efficiency improves, but inconvenience to other road users increases
Solution Approach 1:
The vehicle dynamically adjusts its queuing behavior based on real-time conditions, using trained models to predict whether joining a queue would be beneficial and to determine the appropriate moment to join or skip the queue, enabling flexible adaptation to varying traffic situations
Solution Approach 2:
The vehicle uses sensor data and trained models to predict queue formations before they fully develop and determines in advance whether to join or skip the queue, allowing proactive rather than reactive decision-making about queuing behavior
3Adaptability or versatility
If autonomous vehicles join queues, then responsiveness to queuing situations improves, but risk of blocking traffic or interfering with loading/unloading increases
Solution Approach 1:
The vehicle continuously monitors sensor data while in the queue to detect changes in traffic conditions and the status of loading/unloading operations, using this feedback to determine when to proceed, wait, or exit the queue to avoid causing harm
Solution Approach 2:
The vehicle uses sensor data and trained models to predict potential harmful effects of joining or remaining in a queue before they occur, and takes preliminary actions to avoid these negative outcomes, such as exiting the queue early if interference with loading/unloading is anticipated
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.