Autonomous Vehicle Dispatch for Weather-Aware Pickup Locations
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Solution Overview
Problem
Autonomous vehicles face challenges in optimizing pick-up and drop-off locations for transportation services, particularly in varying weather conditions, which can impact passenger comfort and experience.
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 adjust these conditions to optimize the selection of second locations for autonomous vehicles, ensuring improved passenger experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If autonomous vehicles select pick-up and drop-off locations without considering weather conditions, then the vehicle operation is simple and efficient, but passenger comfort and experience deteriorate
Solution Approach 1:
The system performs preliminary weather condition assessments and location optimizations before the vehicle arrives at pick-up and drop-off points. By pre-identifying suitable alternative locations based on weather forecasts and real-time conditions, the system prepares comfort-adjusted routes in advance, maintaining operational simplicity while improving passenger experience.
Solution Approach 2:
The system introduces an intermediary optimization layer between the vehicle and the pick-up/drop-off locations. This intermediary system evaluates weather conditions, vehicle state, and location suitability to mediate the selection process, finding balanced solutions that maintain operational efficiency while protecting passengers from adverse weather effects.
2Object-affected harmful factors
If autonomous vehicles adjust internal vehicle state conditions based on weather conditions, then passenger comfort is improved, but device complexity increases
Solution Approach 1:
The system implements a universal weather-response framework that handles multiple vehicle state adjustments (temperature control, window positioning, HVAC settings) through a single integrated decision-making process. This multi-functional approach allows the system to manage various comfort parameters simultaneously without proportionally increasing complexity, as the same weather assessment drives multiple coordinated adjustments.
Solution Approach 2:
The system changes operational parameters (vehicle temperature, window states, HVAC intensity) based on weather condition parameters. By directly mapping weather parameters to vehicle state parameters through predefined relationships and lookup tables, the system achieves adaptive comfort adjustment without requiring complex real-time calculations, thus limiting complexity growth.
3Object-affected harmful factors
If autonomous vehicles determine optimal second locations based on multiple priorities including weather conditions, then user experience is enhanced, but calculation time and processing requirements increase
Solution Approach 1:
The system pre-calculates and stores location suitability data, weather condition thresholds, and priority weightings before runtime. By preparing decision matrices and alternative location lists in advance based on historical weather patterns and location characteristics, the system reduces real-time calculation requirements, enabling fast location determination while still considering multiple priorities including weather conditions.
Solution Approach 2:
The system uses lightweight, approximate location evaluation methods that provide sufficient accuracy for weather-based decisions without requiring computationally intensive precise calculations. By accepting near-optimal solutions that can be quickly determined through simplified models and predefined rules, the system achieves good user experience with minimal processing time and computational resources.
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.