A fuzzy rule-based system for terrain classification in highway design

ABSTRACT

The choice of an incorrect terrain classification might lead to consequences in construction costs, design speed, or even safety. However, the current design criteria for terrain classification may be highly subjective. In Brazil, design guidelines use textual descriptors for three classes, namely level, rolling, and mountainous. This study proposes a fuzzy rule-based classifier to predict terrain classes based on average slope and slope variation. The classifier uses fuzzy logic, which can account for imprecise and vague definitions of the input variables. The classifier was built using topographic variables, i.e. slope variation and average slope, and experts’ knowledge. A survey was considered to extract experts’ opinions regarding different terrain classes. The classifier provided an accuracy of at least 75%, which suggests that the expert system captured the experts’ perceptions of the highway classes. As a result, the proposed system can assist decision-making by providing a more consistent method for terrain classification.

KEYWORDS:

• Infrastructure design
• terrain classification
• fuzzy logic
• highways
• rule-based system

Data availability statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Disclosure statement

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