Safety Routing Using Lighting Metrics for Night Pickup Paths
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Solution Overview
Problem
Users and drivers face challenges in determining safe pickup and drop-off locations and routes due to unsafe conditions such as theft, assaults, potholes, and poor lighting, especially in unfamiliar areas, with existing systems lacking the ability to assess and prioritize safety based on lighting metrics.
Innovation Solution
A system that utilizes satellite imagery and geospatial vector datasets to analyze lighting metrics and generate safety scores for pickup and drop-off locations and routes, integrating accident data to identify safe locations and routes with ample nighttime lighting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional routing systems are used without safety analysis, then route selection is fast and simple, but safety cannot be ensured especially during nighttime travel
Solution Approach 1:
The system performs preliminary safety analysis by analyzing satellite imagery to determine lighting metrics for various routes before the user requests transportation. Safety scores are pre-calculated and stored, so when a ride request comes in, the system can quickly retrieve and use the pre-analyzed safety information without performing complex real-time analysis, thus ensuring safety while maintaining operational speed.
2Measurement precision
If comprehensive safety analysis including satellite imagery analysis is performed, then lighting metrics and safety scores can be accurately determined, but computational resources and time are consumed
Solution Approach 1:
The system performs comprehensive safety analysis in advance by analyzing satellite imagery and calculating lighting metrics for all possible routes between pickup and drop-off locations before users request rides. These pre-calculated safety scores are stored and can be quickly retrieved when needed, achieving both high measurement precision and fast response time.
Solution Approach 2:
The system focuses analysis on specific local characteristics of each route segment, particularly lighting conditions at different locations. By evaluating lighting metrics locally for each segment rather than treating the entire route uniformly, the system achieves precise safety assessment while optimizing computational resources through targeted analysis of critical areas.
3Reliability
If safety scores are calculated for all candidate routes, then the safest route can be identified, but computational complexity increases
Solution Approach 1:
The system divides the route evaluation process into segments, analyzing lighting metrics and safety conditions for each individual route segment separately. By segmenting the overall route into smaller manageable parts and calculating safety scores for each segment independently, the system can comprehensively evaluate all candidate routes without being overwhelmed by computational complexity, as each segment can be processed independently and efficiently.
Data Source
AI summary
Systems and methods are provided to receive a request for service indicating a start location and a destination location for the service, determine that a time of day for the request for service triggers a safety analysis, and analyze the start location and destination location to identify a pickup location to start the service and a drop-off location to end the service based on lighting metrics associated with the pickup location and the drop-off location. The systems and methods further generate a plurality of candidate routes for the service from the pickup location to the drop-off location, generate a safety score for each candidate route of the plurality of candidate routes by identifying a lighting metrics based on pixel values in imagery for each segment of each candidate route and select a route for the service based on a least the safety score of each candidate route.