Developing a Traffic Congestion Model based on Google Traffic Data: A Case Study in Ecuador

Yasmany García-Ramírez

Abstract

Congestion on urban streets has negative impacts on the urban economy, environment, and lifestyle. Congestion, in developing countries, will increase despite knowing its cons. One way to control or reduce congestion is by sharing traffic information through traffic model congestion. This model includes the estimation of the travel time from the desired place of origin-destination. Speed-flow-density parameters help to calculate travel time. These fundamental parameters could be estimated using Floating Car Data from Google. Therefore, the objective of this research is to calibrate equations for the fundamental parameters with traffic state indicators by Google, relating them to ground truth data. Six density-flow equations and six speed-density equations were calibrated using power and linear curve, and some of them were validated. Other cities can use these equations to build their traffic congestion model. With this model, road users can plan the journey and choice the best route or travel in times of low congestion or uptake of public transport, decongesting the city and saving traffic costs related. This comprehensive research extends the knowledge of how Google traffic information can employ in developing cities.

Download


Paper Citation


in Harvard Style

García-Ramírez Y. (2020). Developing a Traffic Congestion Model based on Google Traffic Data: A Case Study in Ecuador.In Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-419-0, pages 137-144. DOI: 10.5220/0009594501370144


in Bibtex Style

@conference{vehits20,
author={Yasmany García-Ramírez},
title={Developing a Traffic Congestion Model based on Google Traffic Data: A Case Study in Ecuador},
booktitle={Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2020},
pages={137-144},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009594501370144},
isbn={978-989-758-419-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Developing a Traffic Congestion Model based on Google Traffic Data: A Case Study in Ecuador
SN - 978-989-758-419-0
AU - García-Ramírez Y.
PY - 2020
SP - 137
EP - 144
DO - 10.5220/0009594501370144