Dynamic Road Hierarchy for Real-Time Traffic Routing
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Solution Overview
Problem
Current digital map systems face inefficiencies in processing large volumes of real-time traffic data, leading to increased computational complexity and response time, especially under severe traffic conditions, due to the limitations of pre-computed hierarchies and static link cost algorithms.
Innovation Solution
The system employs dynamically adaptive hierarchies by creating multiple environmental profiles based on real-time traffic conditions and user parameters, merging these profiles into a single hierarchy, and using cluster-routing to approximate travel costs, while dynamically adding links and adjusting the hierarchy in response to real-time data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If pre-computed hierarchies and static link cost algorithms are used, then routing computation is simplified, but computational complexity and response time increase under severe traffic conditions
Solution Approach 1:
The patent transforms the static routing hierarchy into a dynamic structure that adapts to real-time traffic conditions. The system continuously updates link costs and hierarchy levels based on current traffic data, allowing the routing computation to remain efficient while responding to changing conditions. This dynamic adaptation resolves the contradiction by making the complexity manageable through selective updates rather than complete recomputation.
Solution Approach 2:
The system changes key parameters such as link costs and hierarchy levels based on real-time traffic conditions. By dynamically adjusting these parameters rather than using static values, the system can respond to traffic changes without requiring complete recomputation of the routing hierarchy, thus reducing both computational complexity and response time under severe traffic conditions.
2Measurement precision
If real-time traffic data is processed in detail, then routing accuracy improves, but computational complexity increases
Solution Approach 1:
The patent extracts only the most relevant features from real-time traffic data for routing decisions. Rather than processing all available traffic data in detail, the system identifies and uses key parameters such as link costs and hierarchy levels that have the greatest impact on routing accuracy. This selective extraction maintains routing accuracy while significantly reducing computational complexity.
Solution Approach 2:
The system applies partial processing to traffic data by focusing computational resources on the most critical links and hierarchy levels that affect routing decisions. By not processing every detail of traffic data uniformly, but rather applying selective processing where it matters most, the system achieves good routing accuracy without the full computational burden of detailed processing everywhere.
3Speed
If static link cost algorithms are used, then computational speed is maintained, but adaptability to real-time traffic conditions deteriorates
Solution Approach 1:
The patent implements dynamic link cost algorithms that adapt to real-time traffic conditions while maintaining computational efficiency. The system updates link costs based on current traffic data and adjusts hierarchy levels dynamically, allowing fast computation speeds to be maintained through selective updates rather than complete recomputation, thus achieving both speed and adaptability.
4Measurement precision
If comprehensive routing options are considered, then routing accuracy improves, but response time increases
Solution Approach 1:
The patent segments the routing computation process into hierarchical levels, where higher-level links are processed first and lower-level links are considered only when necessary. This segmentation allows the system to quickly evaluate comprehensive routing options at higher levels and only delve into detailed lower-level options when needed, thus maintaining routing accuracy while reducing overall response time.
Data Source
AI summary
A system and method for computing routing on a road network are described. One embodiment includes pre-processing routing data for one or more environmental profiles integrated into a hierarchy, dynamically adding links to the hierarchy in response to real-time data on traffic conditions, and cluster-routing to approximate routing travel costs based on realtime traffic data A further embodiment includes a) identifying one or more portions of a road network as being more preferable than normal based on real-time data, b) expressing the one or more portions of the road network as a sequence of locations comprising a uniquely identifiable path, c) using the sequence of locations comprising a uniquely identifiable path to add one or more links to an already constructed hierarchical network of roads, and d) enabling a pathfinding algorithm to adjust to the real-time data.