DOAJ Open Access 2025

Development of Representative Urban Driving Cycles for Congested Traffic Conditions in Guayaquil Using Real-Time OBD-II Data and Weighted Statistical Methods

Roberto López-Chila Henry Abad-Reyna Joao Morocho-Cajas Pablo Fierro-Jimenez

Abstrak

Standardized driving cycles such as the FTP-75 fail to represent traffic conditions in cities like Guayaquil, where high congestion and varied driving behaviors are not captured by external models. This study aimed to develop representative driving cycles for the city’s most congested urban routes, covering the north, south, center, and west zones. Using the direct method, real-world trips were conducted with an M1-category vehicle equipped with an OBDLINK MX+ device, allowing real-time data collection. Driving data were processed through OBDWIZ software Version 4.30.1 and statistically analyzed using Minitab. From pilot tests, the appropriate sample size was estimated, and normality tests were applied to determine the correct measures of central tendency. The final representative cycles were constructed using a weighting criteria method. The results provided quantified evidence of variations in average speed, idle time, and acceleration patterns across the routes, which were transformed into representative driving cycles. These cycles provide a more accurate basis for emission modeling, vehicle certification, and transport policy design in congested cities such as Guayaquil, and this is the applied impact that is highlighted in our contribution. Furthermore, the developed cycles provide a foundation for future research on emission modeling and the design of sustainable transport strategies in Latin American cities.

Penulis (4)

R

Roberto López-Chila

H

Henry Abad-Reyna

J

Joao Morocho-Cajas

P

Pablo Fierro-Jimenez

Format Sitasi

López-Chila, R., Abad-Reyna, H., Morocho-Cajas, J., Fierro-Jimenez, P. (2025). Development of Representative Urban Driving Cycles for Congested Traffic Conditions in Guayaquil Using Real-Time OBD-II Data and Weighted Statistical Methods. https://doi.org/10.3390/vehicles7030095

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Informasi Jurnal
Tahun Terbit
2025
Sumber Database
DOAJ
DOI
10.3390/vehicles7030095
Akses
Open Access ✓