Development of a Digital Road Database for Pavement Condition Assessment and Safe Speed Recommendation Based on Field Diagnostics

The increasing demands for road safety and digitalization of transport infrastructure require advanced approaches for pavement condition assessment and information support for road users. This study aims to develop a digital road database based on field diagnostics for evaluating pavement condition and generating preliminary driving recommendations based on pavement operational condition. Field investigations were conducted on the Kostanay–Auliekol highway and the Western Europe–Western China international transport corridor. The methodology included visual inspections, measurements of pavement structural capacity using the MADI-CNIIL deflectometer and Benkelman beam, and pavement roughness evaluation using the TED-2M bump integrator and the International Roughness Index (IRI). The results showed that pavement strength coefficients ranged from 0.89 to 0.97, while IRI values varied between 1.2 and 2.0 m/km. A strong correlation between TED-2M readings and IRI values (R2 = 0.9848) was established. A digital road database structure was developed to support pavement condition visualization, road safety assessment, and intelligent transportation systems.