Autonomous Vehicle Route Control Using Astronomical Lighting Prediction
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Solution Overview
Problem
Autonomous vehicles face safety issues due to poor lighting conditions, as sensors like cameras struggle to perceive the environment effectively at night, during overcast weather, or in stormy conditions, leading to potential unsafe operation.
Innovation Solution
A system that predicts lighting condition changes using local astronomical data, such as sunset times, to determine the probability of completing a planned route within safe operating conditions, and generates commands to adjust vehicle actions, such as re-routing or stopping, if the probability falls below a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle operates in poor lighting conditions (night, overcast, stormy weather), then the vehicle can maintain route completion and operational continuity, but the sensor perception capability deteriorates leading to unsafe operation
Solution Approach 1:
The system performs preliminary action by predicting lighting conditions along the planned route using astronomical data (sunrise/sunset times, moon phase, cloud cover forecasts) before the vehicle encounters poor lighting conditions. This allows the vehicle to proactively adjust its operation, such as delaying departure, selecting alternative routes with better lighting, or notifying the user, thereby avoiding unsafe sensor operation in the first place
Solution Approach 2:
The system establishes feedback by continuously monitoring current lighting conditions, comparing them against the predicted conditions for the planned route, and adjusting the vehicle's operational status accordingly. The controller uses this feedback loop to determine whether to proceed with the planned route, modify it, or delay operation to maintain safety while preserving route completion capability
2Reliability
If the vehicle delays or modifies the planned route to avoid poor lighting conditions, then sensor perception safety is improved, but the time to complete the route increases
Solution Approach 1:
The system applies dynamics by providing flexible, adaptive route management that can dynamically adjust the planned route based on predicted lighting conditions. The controller evaluates multiple potential routes and timing options, selecting the optimal combination that maintains safety while minimizing time loss. This may involve suggesting alternative routes with better lighting forecasts or optimizing departure times to coincide with favorable lighting conditions
Solution Approach 2:
The system changes parameters by adjusting operational parameters such as departure time, route selection, and driving schedule based on predicted lighting conditions. Rather than rigidly adhering to a fixed route and time, the system modifies these parameters proactively to ensure safe sensor operation, balancing safety requirements with efficient route completion
Data Source
AI summary
Methods and systems for determining an action for a vehicle. The system includes an electronic controller configured to determine a planned route of the vehicle, determine local astronomical data based upon the planned route, compare the local astronomical data to the planned route of the vehicle to determine a probability of completion of the planned route, and if the probability of completion is below a threshold, generate a command indicating an action for the vehicle.