From Electronic Toll Records to Structural Number: A Data-to-Design Framework and Readiness Classification for Flexible Pavement Design

Traffic loading strongly influences the structural design of flexible pavements, yet in many developing countries the electronic toll collection (ETC) systems that record heavy-vehicle movements continuously are used almost exclusively for revenue administration. This study asks how continuously collected toll records can be converted into inputs for flexible pavement design and asset management, and answers it with a Data-to-Design Implementation Framework and a four-tier data readiness classification. A single embedded case study was conducted at the Shimabala Toll Plaza on the Lusaka–Chirundu corridor (road T2), Zambia, using electronic toll records for 2023 and 2024 and an automatic axle classification count. Load equivalency factors were derived from the SADC legal axle-group loads for two load states. The 2023 base-year Annual Average Daily Truck Traffic was 1538 heavy vehicles per day, the annual design-lane loading was 1.33 × 106 Equivalent Single Axle Loads (ESALs) in a fully laden, legal-limit scenario, and cumulative design traffic over 20 years was 2.66 × 107 ESALs at zero growth and 4.39 × 107 at 5% compound growth. A layered AASHTO (1993) solution requires structural numbers of 5.46 to 5.84, satisfied by 220 to 240 mm of asphalt concrete over granular base and subbase. A Monte Carlo analysis gives a median required structural number of 5.51 (90% interval 4.83 to 6.46); subgrade strength dominates and overloading ranks highest among the traffic parameters, while the order of load state and growth depends on the assumed ranges. The take-away for the pavement industry is that toll data supply a complete, low-cost record of demand but not of axle load, so road authorities should retain axle counts in toll transactions and calibrate equivalency factors with weigh-in-motion data before relying on toll-derived loading.