Travel time prediction on signalised urban arterials by applying SARIMA modelling on Bluetooth data

Khoei, Amir Mohammad, Bhaskar, Ashish, & Chung, Edward (2013) Travel time prediction on signalised urban arterials by applying SARIMA modelling on Bluetooth data. In 36th Australasian Transport Research Forum (ATRF) 2013, Queensland University of Technology, Brisbane, QLD.

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Abstract

Travel time prediction has long been the topic of transportation research. But most relevant prediction models in the literature are limited to motorways. Travel time prediction on arterial networks is challenging due to involving traffic signals and significant variability of individual vehicle travel time. The limited availability of traffic data from arterial networks makes travel time prediction even more challenging.

Recently, there has been significant interest of exploiting Bluetooth data for travel time estimation. This research analysed the real travel time data collected by the Brisbane City Council using the Bluetooth technology on arterials. Databases, including experienced average daily travel time are created and classified for approximately 8 months. Thereafter, based on data characteristics, Seasonal Auto Regressive Integrated Moving Average (SARIMA) modelling is applied on the database for short-term travel time prediction.

The SARMIA model not only takes the previous continuous lags into account, but also uses the values from the same time of previous days for travel time prediction. This is carried out by defining a seasonality coefficient which improves the accuracy of travel time prediction in linear models. The accuracy, robustness and transferability of the model are evaluated through comparing the real and predicted values on three sites within Brisbane network. The results contain the detailed validation for different prediction horizons (5 min to 90 minutes). The model performance is evaluated mainly on congested periods and compared to the naive technique of considering the historical average.

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ID Code: 63176
Item Type: Conference Paper
Refereed: Yes
Keywords: Travel time prediction, SARIMA modelling, Arterial travel time, Bluetooth data, Time series analysis
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Transport Engineering (090507)
Divisions: Current > Schools > School of Civil Engineering & Built Environment
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Current > Research Centres > Smart Transport Research Centre
Copyright Owner: Copyright 2013 [please consult the author]
Deposited On: 17 Nov 2013 22:53
Last Modified: 19 Nov 2013 10:25

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