M.B. Sushma, S. Roy, A. Maji
Highway corridor planning is a preliminary and primary step in the planning and development of highways where land parcels are demarcated to be subsequently surveyed for developing the final alignment. The traditional approach, where the experts study topographic, and land use maps to identify potential corridors, relies on human judgment and intuition and can either miss-select the best alternative or yield the best local corridors. This might result in developing sub-optimal highway alignments, thus affecting the highway development process. This paper proposes a Geographic Information Systems (GIS) integrated artificial intelligence-based heuristic optimization method to identify the highway corridor for a detailed alignment development. Using the Halton sequence-based low-discrepancy point sampling method, potential intermediate points are developed in a GIS map with land use, elevation, and cost information. Each segment, represented by an enclosed intermediate point, inherits the corresponding land parcel property, elevation, and environment-sensitive locations. Using the ant algorithm (AA), these segments are joined between the two desired locations to form a wide strip of land parcels representing the highway corridor. The efficacy of the proposed model is demonstrated in a real-world case study from the city of Pune, India, where the model yielded a corridor that avoided the environment-sensitive areas and had minimum cost. The method was also able to generate diverse alternative routes with comparable cost and impact, so the stakeholders can choose routes by varying corridor objectives. The analysis results also show that the right-of-way cost and impacted land parcels increased outside the boundary of the developed corridors. Overall, the proposed model can benefit the existing highway development policy by eliminating the repetitive and resource-intensive manual process, the resulting biases in identifying the survey areas, and explicitly specifying the corridor that might be explored for the optimized alignment design.
Keywords: GIS; Artificial Intelligence; Ant algorithm; highway corridor; Voronoi diagram; Halton sequence; highway alignment; optimized highway corridor planning