Horizontal Alignment Optimization Using 3D Terrain Grids
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Solution Overview
Problem
Current methods for determining optimal horizontal alignments in road design are inefficient and do not effectively consider terrain complexity, environmental factors, and multiple cost factors, leading to suboptimal construction and maintenance costs.
Innovation Solution
An automated method that uses terrain data, constraint data, and cost data to find an optimal alignment by minimizing costs through a combination of Dijkstra's shortest path method, Segmented Least Squares, and Douglas-Peucker methods, while respecting design constraints and incorporating soft costs, using a Covariance Matrix Adaptation Evolution Strategy for optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional two-stage alignment design is used, then design simplicity is maintained, but optimization effectiveness deteriorates
Solution Approach 1:
The patent merges horizontal and vertical alignment design into a unified three-dimensional optimization process. The system simultaneously optimizes both horizontal coordinates (x, y) and vertical coordinate (z) by integrating terrain data, earthwork cost calculations, and alignment geometry into a single computational model, eliminating the need for sequential two-stage design while achieving superior optimization results
Solution Approach 2:
The patent transitions from traditional two-dimensional horizontal alignment design to three-dimensional alignment optimization by incorporating vertical elevation data and terrain information. The system evaluates alignments in 3D space considering ground surface elevations, cut-fill volumes, and vertical geometry constraints, adding a critical dimension that was previously handled separately or ignored
2Manufacturing precision
If comprehensive cost factors are considered, then alignment optimization quality is improved, but computational complexity increases
Solution Approach 1:
The patent segments the total cost function into distinct components: earthwork costs (cut and fill), construction costs, land acquisition costs, and environmental costs. Each component is calculated separately using specific formulas and then aggregated into a total cost metric, allowing the system to comprehensively evaluate multiple factors while maintaining computational tractability through modular processing
Solution Approach 2:
The system dynamically adjusts geometric parameters of the alignment (curvature, gradient, length) during optimization iterations to minimize the comprehensive cost function. The optimization algorithm modifies alignment coordinates and vertical profile parameters iteratively, evaluating cost changes resulting from each parameter adjustment until convergence to the optimal alignment is achieved
3Object-affected harmful factors
If environmental constraints are enforced, then environmental impact is reduced, but design flexibility deteriorates
Solution Approach 1:
The patent introduces an environmental cost function as an intermediary mechanism that quantifies environmental impact in monetary or numerical terms. This mediator translates qualitative environmental constraints (protected areas, wetlands, cultural sites) into quantitative penalties that are integrated into the total cost function, allowing the optimizer to balance environmental protection with design flexibility through weighted cost minimization rather than rigid constraint enforcement
Data Source
AI summary
A method, apparatus, system, article of manufacture, and computer program product provide the ability to optimize a transport alignment. Terrain data, constraint data, and cost data are read. Terrain pixels having elevation values are organized and stored in a first grid structure with rows and columns that enable efficient access to each terrain pixel. One or more raster layers of a same dimension and orientation as the first grid structure are created. A starting alignment is obtained. The starting alignment is then optimized using the one or more raster layers.