Multi-Feature-Based Road Complexity Calculation Model for the Evaluation of Unmanned Ground Vehicles

To achieve the quantitative assessment of unmanned ground vehicles, it is necessary to quantitative analysis of the test environment. As an important part of the environmental factors, road has a major impact on test and evaluation for unmanned ground vehicles. However, previous studies on road are mainly based on the concept of road roughness. Because of the unicity of road feature indicators, road complexity can only be reflected to a certain extent. In order to show the complexity of road more comprehensively, this paper proposes a multi-feature-based road complexity calculation model in off-road environment. First, a multi-sensor-based data acquisition mobile platform is established to obtain more complete road data. Then, based on the analysis of road feature, road indicators like road roughness, average slope and adhesion characteristics of travelable area are obtained. According to the analysis methods of road roughness, the principle of analytic hierarchy process and the data collected from off-road environment, the calculation model of road complexity is determined. Finally, by calculating complexities of cross-country roads, the feasibility of this model is verified. The result shows that this model can quantitatively analyze road complexity in off-road environment and provide a theoretical support for the scientific calculation of different road complexities.