Autonomous Vehicle Pullover Spot Vacancy Prediction for Pickup Waiting
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Solution Overview
Problem
Autonomous vehicles face challenges in picking up riders or packages due to heavy traffic and limited parking spaces, especially in dense urban environments, where they struggle to determine the best location to wait for a vacating spot or choose an alternative.
Innovation Solution
An autonomous vehicle evaluates signals from its perception system, including vehicle-related and contextual information, to determine if another vehicle will vacate a pullover spot within a selected time, allowing it to wait for that spot or choose an alternative location based on factors like historical parking data, real-time conditions, and impact on other road users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle waits for a pullover spot to become available, then the vehicle can secure an optimal pickup location, but the waiting time increases and may delay the pickup
Solution Approach 1:
The system performs preliminary actions by identifying potential pullover spots in advance and monitoring their occupancy status before the vehicle arrives. The perception system continuously detects whether occupied spots will become available soon, allowing the vehicle to make informed decisions about waiting versus alternative locations, thereby reducing unnecessary waiting time while ensuring optimal spot availability.
2Measurement precision
If the autonomous vehicle monitors multiple signals and attributes to predict spot vacancy, then the accuracy of prediction improves, but the computational complexity and processing time increase
Solution Approach 1:
The system segments the complex prediction task into distinct components: the perception system handles sensor data collection and basic object detection, while the processor separately evaluates multiple attributes (turn signal activation, hazard signal activation, brake light illumination, wheel angle, door/trunk open status, driver/passenger presence) and combines them to determine vacancy likelihood. This segmentation allows each component to specialize, improving overall prediction accuracy while managing computational complexity through modular processing.
3Productivity
If the autonomous vehicle chooses an alternative pullover location instead of waiting, then the pickup can proceed without delay, but the optimal pickup location may not be secured
Solution Approach 1:
The system dynamically adjusts the pickup strategy based on real-time conditions. The processor continuously evaluates the likelihood of spot vacancy using multiple attributes and compares this against the time cost of waiting. If prediction confidence is high and wait time is acceptable, the vehicle waits for the optimal spot; otherwise, it selects an alternative location. This dynamic decision-making balances pickup efficiency with location optimality, adapting to changing traffic and environmental conditions.
Data Source
AI summary
The technology involves to pickups performed by autonomous vehicles. In particular, it includes identifying one or more potential pullover locations adjacent to an area of interest that an autonomous vehicle is approaching. The vehicle detects that a given one of the potential pullover locations is occupied by another vehicle and determines whether the other vehicle will be vacating the given pullover location within a selected amount of time. Upon determining that the other vehicle will be vacating the given potential pullover location within the timeframe, the vehicle determines whether to wait for the other vehicle to vacate the given pullover location. Then a driving system of the vehicle either performs a first action in order to wait for the other vehicle to vacate the given pullover location or performs a second action that is different from the first action when it is determined to not wait.