Route Calculation Graph Transformation for Speed Profiles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing route calculation methods struggle to accurately and efficiently account for continuous speed transitions between edges in a graph, leading to path-dependent weights that are difficult to compute, especially for electric vehicles where energy consumption is a critical factor.
Innovation Solution
The method transforms the initial graph by adding edges at nodes with speed changes, allowing path-independent weights to be assigned, enabling the use of conventional algorithms like Dijkstra for efficient route calculation while considering speed profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous speed transitions between edges are taken into account in route calculation, then measurement precision of energy consumption and travel time is improved, but device complexity increases due to path-dependent weights requiring specialized algorithms
Solution Approach 1:
The method segments the continuous speed transition problem into discrete components by introducing virtual nodes at specific locations (e.g., intersections, speed change points) along edges. This divides the path-dependent weight calculation into manageable segments that can be processed using standard algorithms, thereby maintaining measurement precision while reducing algorithmic complexity.
Solution Approach 2:
The patent transforms the one-dimensional edge-based graph into a two-dimensional node-based graph by adding virtual nodes. This dimensional transformation allows path-independent weights to be assigned to edges in the expanded graph, enabling the use of conventional algorithms like Dijkstra while still capturing continuous speed transition effects.
2Measurement precision
If path-dependent weights are used to account for speed profiles, then measurement precision of travel time is improved, but productivity decreases due to limited availability of efficient calculation algorithms
Solution Approach 1:
The method performs preliminary actions by pre-calculating and storing speed profile data, acceleration rates, and other parameters at virtual nodes before route calculation. This preprocessing allows the main routing algorithm to operate efficiently with path-independent weights while still incorporating continuous speed transition effects, thereby improving both precision and calculation speed.
Solution Approach 2:
The patent creates a copy of the original graph structure with added virtual nodes and edges, where path-independent weights can be assigned. This copied graph structure allows conventional algorithms to run efficiently while the weighting scheme in the copied graph reflects the continuous speed transitions of the original problem.
3Measurement precision
If speed profiles with continuous transitions are considered, then measurement precision of energy consumption is improved, but device complexity increases due to path-dependent weight requirements
Solution Approach 1:
Virtual nodes act as intermediaries between adjacent edges with different speed characteristics. These intermediary nodes capture the continuous speed transition effects and allow path-independent weights to be assigned to the edges connecting them, thereby improving energy consumption measurement precision without requiring path-dependent weight structures.
4Productivity
If conventional algorithms like Dijkstra are used with path-independent weights, then productivity is improved, but measurement precision deteriorates due to inability to account for continuous speed transitions
Solution Approach 1:
The patent changes the parameters associated with graph elements by introducing virtual nodes that carry speed profile information. This parameter enrichment allows conventional algorithms to operate efficiently while the enhanced parameters (speed, acceleration, energy consumption rates) enable precise calculation of travel time and energy consumption that accounts for continuous speed transitions.
Data Source
Figure 1~3
Figure 4
Figure 5
AI summary
The method involves obtaining an initial graph (100) which reflects a road network including nodes (150,151c) and edges (160c,160d). The initial graph is transformed to a result-graph (101) with an added edge (161c) for connecting an input edge (160a) to an output edge (160c) of the node (150). The travel speed (200) of the node, the input edge and the output edge are determined. The weights for the edges and the node of the result-graph are calculated from the determined travel speed. The route is calculated based on the specific weights from the result-graph. An independent claim is included for a navigation apparatus.