Lane Occupancy Analysis for Multi-Lane Roadway Navigation
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Solution Overview
Problem
Current navigation platforms cannot effectively provide navigation instructions to vehicles to optimize lane occupancy on multi-lane roadways, leading to inefficient travel and increased risk of collisions due to sudden lane changes.
Innovation Solution
A navigation platform that analyzes traffic data from cameras and sensors to determine lane occupancies and provides instructions to vehicles to balance lane usage, allowing them to merge into faster lanes proactively, reducing congestion and collision risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If navigation platforms provide traditional navigation instructions without lane-specific traffic analysis, then the navigation system remains simple, but lane occupancy optimization and travel efficiency are not improved
Solution Approach 1:
The navigation platform performs preliminary analysis of traffic data from multiple cameras and sensors to determine current and future lane occupancies before providing navigation instructions. This advance analysis enables the system to proactively guide vehicles into optimal lanes before congestion occurs, improving travel efficiency without requiring complex real-time decision-making during the navigation event itself
Solution Approach 2:
The patent introduces an intermediary processing layer that analyzes traffic data from multiple sources (cameras, sensors) and translates it into lane occupancy predictions and navigation recommendations. This intermediary layer handles the complexity of multi-source data integration and analysis, keeping the overall system architecture manageable while enabling sophisticated lane optimization capabilities
2Loss of time
If vehicles make sudden lane changes to reach faster lanes, then travel time is reduced, but collision risk increases
Solution Approach 1:
The system performs preliminary analysis to identify faster lanes and calculates optimal merge points before the vehicle reaches them. By providing advance navigation instructions about upcoming lane changes, the system enables drivers to make smooth, planned transitions rather than sudden reactive maneuvers, reducing both time loss and collision risk
Solution Approach 2:
The navigation platform continuously receives feedback from traffic cameras and sensors to update lane occupancy predictions and adjust navigation recommendations. This real-time feedback loop allows the system to monitor traffic conditions and guide vehicles through lane changes safely, preventing collisions by alerting drivers to vehicles in adjacent lanes before they attempt to merge
3Loss of information
If multiple surveillance cameras and sensors are deployed to monitor roadway traffic, then traffic data coverage is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent divides the roadway monitoring into multiple camera positions and sensor locations, with each device responsible for capturing data from a specific segment. The navigation platform then integrates these segmented data sources to create a comprehensive view of lane occupancies across the entire roadway, improving data coverage while maintaining manageable system complexity through modular data collection
Solution Approach 2:
The navigation platform serves multiple functions: it collects data from various sources, analyzes lane occupancies, predicts future traffic conditions, and provides navigation instructions. This multi-functional approach consolidates what would otherwise require separate systems, reducing overall complexity while achieving comprehensive traffic monitoring and optimization
Data Source
AI summary
A navigation platform may receive, from a roadside unit, traffic data associated with a section of a roadway, wherein the section includes a plurality of lanes. The navigation platform may identify, from the traffic data and using a first model, lane data associated with a lane of the plurality of lanes. The navigation platform may determine, based on the lane data, vehicle information associated with the lane, wherein the vehicle information indicates a quantity of vehicles in the lane. The navigation platform may determine a lane occupancy of the lane based on the quantity of vehicles and a capacity of the lane. The navigation platform may determine that a target vehicle is approaching the section. The navigation platform may select, using a second model, a target lane from the plurality of lanes. The navigation platform may perform an action associated with enabling the target vehicle to navigate to the target lane.