A hierarchical model with hexagon grids for multi-objective route planning in large-scale off-road environments

Abstract

Off-road route planning plays a vital role across various domains, including civil transportation, earthquake relief and civil production. Off-road route planning requires the consideration of a diverse range of environmental constraints, which is a considerable challenge compared with conventional route planning along existing networks. We aimed to present a multi-objective route planning method for off-road environments. Specifically, we designed a heuristic function incorporating multiple characteristics to generate reliable route planning solutions based on Pareto optimality. We also constructed a hierarchical hexagonal grid model by merging similar grid cells and reconstructing adjacency relationships with other grid cells to achieve high efficiency. The proposed method was compared with conventional route planning methods using single- and multi-objective approaches in traditional and hierarchical hexagonal grid models. The proposed method can effectively plan off-road routes, improve optimal route distance and trafficability, and provide more efficient route solutions. It reduced the planning time by 97.1% compared with multi-objective route planning based on a traditional hexagonal grid model.

Keywords:

• Off-road route planning
• multi-objective
• hierarchical
• hexagonal grid model

Acknowledgements

The authors would like to thank the anonymous reviewers for their insightful comments that greatly helped improve this study.

Author contributions

Zhanlong Chen conceived the idea, secured the funding, supervised the study and revised the manuscript. Beibei Wu conducted the study and wrote the manuscript. Xiechun Lu and Binghe Xiao commented and revised the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data and codes availability statement

The data and code that support the findings of this study are available at: https://doi.org/10.6084/m9.figshare.23635212.v1

Additional information

Funding

This study was supported by the National Natural Science Foundation of China (No. 41871305); the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education and the Fundamental Research Funds for the Central Universities (No. CUG2022ZR06).

Notes on contributors

Beibei Wu

Beibei Wu is a graduate student in the National Engineering Research Center of Geographic Information System, China University of Geoscience (Wuhan). His research interests include spatial analysis and application of GIS.

Zhanlong Chen

Zhanlong Chen is currently a professor in the School of Computer Science, China, University of Geosciences (Wuhan). His research interests include: spatial representation, spatial analysis and query, spatial cognition and spatial reasoning.

Xiechun Lu

Xiechun Lu is a PhD student in the Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences (Wuhan). His research interests include map generalization and geospatial scene generation.

Binghe Xiao

Binghe Xiao is a graduate student in the Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences (Wuhan). His research interests include off-road route Planning and geospatial analysis.