Vehicle Classification to See the Effect of Damage on Flexible Pavement

Pastrana E.L.; Centty M.V.S.; Marmanillo M.H.S.; de la Cruz J.G.V. · Civil Engineering and Architecture (2024) · DOI: 10.13189/cea.2024.120426

Resumen

According to the National Institute of Statistics and Informatics (INEI) in the technical report N°5-May 2023, the number of light and heavy vehicles through toll booths grew by 2.4%, resulting in traffic congestion and pavement damage due to the lack of adequate vehicle counting control. This work developed a vehicle classification system to assess damage to the flexible pavement of the Universidad del Centro del Perú (UNCP) roads. For the programming of the vehicle classification system, the recording area was located using Google Earth Pro, then the vehicles to be classified were established as car, van, bus, trailer, which were trained by the neural network through 50 iterations, which was done in conjunction with Python where the programming of vehicle counting was performed; while to assess the pavement damage, the data obtained from the field of manual counting and simulation was required to obtain the equivalent factor that is a function of the type of axle and weight of each vehicle. Finally, there was a 19% deficiency in the vehicle classification of cars and the damage to the flexible pavement was determined by considering the manual count and the programmed system count, for which in both cases it was found that the vehicle that damages the flexible pavement is the cars, with 23.22% of damage in the one-way lane in the manual count and 49.49% in the system count.

Instituciones: Universidad Continental