Abstract
This study investigated the challenges of calibration of the PARAMICS microscopic simulation model for the local traffic conditions in the Kingdom of Saudi Arabia. It proposed an adaptive neuro-fuzzy inference system (ANFIS) based calibration protocol for the PARAMICS model. The developed ANFIS model performs adequately in modeling the queue length as a function of two key calibration parameters, namely mean headway time and mean reaction time. The selected values of the calibration parameters obtained through the ANFIS modeling approach were used as the input parameters for the PARAMICS model. The error indices such as mean absolute errors and mean absolute percentage errors of the developed ANFIS model in predicting the queue lengths varied between 1.11 and 1.24, and between 3.44 and 4.06, respectively. The conformance of the PARAMICS output and the measured queue length indicates the validity of the proposed calibration protocol.
| Original language | English |
|---|---|
| Pages (from-to) | 361-368 |
| Number of pages | 8 |
| Journal | Canadian journal of civil engineering |
| Volume | 43 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2016 |
Bibliographical note
Publisher Copyright:© 2016, National Research Council of Canada. All rights reserved.
Keywords
- Adaptive neuro-fuzzy inference system (ANFIS)
- Microscopic model calibration
- Microscopic simulation model
- PARAMICS model
- Saudi Arabia
ASJC Scopus subject areas
- Civil and Structural Engineering
- General Environmental Science