Adaptive Street Lighting for Autonomous Vehicle Visibility
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating through varying environmental conditions such as changes in illumination and weather, which can lead to system failures and increased collision risks due to suboptimal lighting conditions.
Innovation Solution
The system dynamically adjusts infrastructure lighting conditions, such as streetlights, by using sensors to collect environmental data and adjust light intensity and direction to optimize illumination levels for autonomous vehicle navigation, reducing the need for redundant vehicle sensors and improving safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If infrastructure lighting is statically configured, then energy consumption is high and light pollution increases, but autonomous vehicle navigation performance remains suboptimal in varying environmental conditions
Solution Approach 1:
The patent implements dynamic adjustment of infrastructure lighting by controlling LED streetlights to vary illumination intensity and color temperature based on real-time environmental conditions detected by sensors. The system transitions from static lighting configuration to dynamic adaptive lighting, adjusting parameters such as brightness and color spectrum according to ambient light levels, weather conditions, and autonomous vehicle presence, thereby optimizing navigation reliability while reducing energy consumption.
Solution Approach 2:
The system changes physical parameters of the lighting infrastructure, specifically adjusting illumination intensity (lumens) and color temperature (Kelvin) dynamically. Sensors detect environmental parameters such as ambient light levels, weather conditions, and vehicle proximity, then the control system modifies lighting parameters accordingly - increasing intensity during poor visibility conditions to improve autonomous vehicle sensor performance and reducing intensity during optimal conditions to conserve energy and reduce light pollution.
2Reliability
If infrastructure lighting is dynamically adjusted to optimize autonomous vehicle navigation, then navigation reliability improves, but system complexity increases
Solution Approach 1:
The infrastructure lighting system performs multiple functions: it provides illumination for public safety, optimizes navigation conditions for autonomous vehicles, reduces energy consumption, and minimizes light pollution. The same LED streetlights and control infrastructure serve both traditional municipal lighting purposes and specialized autonomous vehicle assistance, eliminating the need for separate dedicated lighting systems and reducing overall system complexity.
Solution Approach 2:
The system employs autonomous control where sensors continuously monitor environmental conditions and automatically adjust lighting parameters without human intervention. The control system self-regulates illumination intensity and color temperature based on real-time data from light sensors, weather sensors, and vehicle detection systems, making the infrastructure self-adaptive and reducing the need for complex manual control mechanisms.
3Measurement precision
If lighting intensity is increased to improve visibility for autonomous vehicles, then detection accuracy improves, but energy consumption and light pollution increase
Solution Approach 1:
The lighting system operates in periodic cycles, adjusting intensity based on detected environmental conditions rather than maintaining constant high illumination. During periods of optimal natural lighting or clear weather, the system reduces or turns off supplemental lighting. During periods of poor visibility (night, fog, rain), the system increases intensity. This periodic adjustment based on real-time conditions optimizes detection accuracy while minimizing energy consumption and light pollution during periods when high illumination is not needed.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the performance of autonomous vehicles by minimizing risks associated with poor lighting conditions, reducing driver fatigue, and lowering accident rates, while also conserving energy and reducing light pollution.
Implementation Method 1
using sensors to collect environmental data
Implementation Method 2
adjust light intensity and direction to optimize illumination levels
Data Source
AI summary
Disclosure herein are systems and methods for dynamically adjusting infrastructure items, such as street lights, construction signage, and/or other lighting elements. The systems and methods may include receiving environmental data for a sector containing the infrastructure items. A quality of infrastructure effectors located within the sector may be determined. A deviation from a standard infrastructure quality associated with the infrastructure effectors may be determined. A setting of the infrastructure items located in the sector may be changed to minimize the deviation from the standard infrastructure quality.