Autonomous Vehicle Trip Dispatch for Weather-Aware Pickup Routing
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Solution Overview
Problem
Autonomous vehicles face challenges in optimizing pick-up and drop-off locations for passengers and goods, especially in varying weather conditions, which can impact user experience and vehicle operations.
Innovation Solution
A method is implemented where server computing devices receive trip requests, determine weather conditions at initial locations, identify internal vehicle state conditions and priorities based on weather, and then determine alternative locations for autonomous vehicles to adjust their internal state and optimize trip routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If autonomous vehicles use fixed pick-up and drop-off locations, then operational simplicity is maintained, but user comfort and safety deteriorate in adverse weather conditions
Solution Approach 1:
The system dynamically adjusts pick-up and drop-off locations based on real-time weather conditions. Instead of using fixed locations, the autonomous vehicle computing devices receive weather data and automatically modify the vehicle's route and stopping points to avoid adverse conditions like rain, snow, or extreme temperatures, thereby maintaining operational simplicity while improving user comfort.
Solution Approach 2:
The system performs preliminary weather condition assessments before the vehicle arrives at pick-up or drop-off locations. By checking weather forecasts and real-time conditions in advance, the system can pre-determine alternative locations that will be safer and more comfortable for passengers, preventing exposure to harmful weather conditions before they occur.
2Object-affected harmful factors
If autonomous vehicles adjust pick-up and drop-off locations based on weather conditions, then user comfort is improved, but system complexity increases
Solution Approach 1:
The system introduces a weather data intermediary layer that acts as a mediator between the autonomous vehicle's navigation system and external weather conditions. This intermediary component receives weather data from external sources, processes it according to predefined criteria, and translates it into location adjustment instructions for the vehicle, thereby managing system complexity through modular design.
Solution Approach 2:
The system changes operational parameters (pick-up and drop-off locations) based on weather condition parameters. By establishing clear relationships between weather parameters (temperature, precipitation, wind speed) and location selection criteria, the system manages complexity through parameter-based decision-making rather than requiring complex algorithms for every possible weather scenario.
3Object-affected harmful factors
If autonomous vehicles continuously monitor weather conditions and adjust locations, then user safety and comfort are improved, but energy consumption increases
Solution Approach 1:
The system implements periodic weather monitoring instead of continuous monitoring. The autonomous vehicle checks weather conditions at predetermined intervals and at key decision points during the trip, such as before approaching pick-up or drop-off locations. This periodic approach maintains user safety and comfort while significantly reducing the energy consumption associated with constant weather data acquisition and processing.
Data Source
AI summary
Aspects of the disclosure provide for arranging trips for autonomous vehicles. For instance, a request for a trip may be received by one or more processors of one or more server computing devices. The request may identify an initial location. A weather condition at the initial location may be identified. One or more internal vehicle state conditions and one or more priorities for pulling over may be determined based on the weather condition. A second location may be determined based on the one or more priorities and the initial location. Dispatch instructions may be provided to an autonomous vehicle, the dispatch instructions identifying the second location and the one or more internal vehicle state conditions in order to cause computing devices of the autonomous vehicle to control the autonomous vehicle to the second location and adjust internal vehicle state conditions based on the one or more internal vehicle state conditions.