Dynamic Road Capacity Calculation for Autonomous Vehicles
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Solution Overview
Problem
Current routing and navigation systems for autonomous vehicles lack accurate and real-time determination of dynamic road capacity data, which is crucial for navigating through congested areas and avoiding traffic jams, especially in scenarios where infrastructure changes are economically impractical.
Innovation Solution
A system and method that utilize probe data, historical traffic patterns, and event data to calculate dynamic road capacity by determining the current count of movable objects, traffic conditions, and congestion thresholds, allowing for timely updates and recommendations for rerouting or lane adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If infrastructure changes such as adding more driving lanes are implemented to increase road capacity, then the road capacity is improved, but the economic feasibility deteriorates significantly
Solution Approach 1:
The patent changes the parameter of road capacity dynamically through software-based lane direction switching and temporary shoulder usage, rather than through permanent physical infrastructure expansion. This allows the road to adapt its capacity parameters in response to traffic conditions without requiring costly construction projects.
Solution Approach 2:
The system implements dynamic lane configuration where lane directions and usage can be changed in real-time based on traffic flow patterns. This dynamic adaptation allows the existing infrastructure to provide variable capacity without permanent modifications, avoiding the economic burden of adding fixed infrastructure.
2Measurement precision
If real-time probe data and historical traffic patterns are analyzed to determine dynamic road capacity, then the accuracy of traffic condition determination is improved, but the computational complexity increases
Solution Approach 1:
The system performs preliminary processing of probe data and historical traffic patterns by maintaining pre-computed traffic profiles and congestion thresholds. This preliminary action reduces the real-time computational burden by having reference data ready before actual traffic condition assessment is needed.
Solution Approach 2:
The patent introduces an intermediary processing layer that aggregates and pre-processes raw probe data into meaningful traffic metrics. This intermediary step simplifies the subsequent analysis by working with processed indicators rather than raw data, reducing overall computational complexity.
Data Source
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AI summary
A system, a method, and a computer program product may be provided for determining dynamic road capacity data of one or more lanes of a road segment in a region. A system may include a memory configured to store computer program code and a processor configured to execute the computer program code to obtain probe data, historical capacity dynamic pattern data and event data. The processor may be configured to calculate road capacity data of the lane. The processor may be configured to calculate a count of movable objects in the lane. The processor may be configured to determine a traffic condition of the lane. The processor may be configured to determine the dynamic road capacity data based on the road capacity data, the count of one or more movable objects, the historical capacity dynamic pattern data and the traffic condition of the at least one lane of the road segment.