Scipediacontent: Scipediacontent moved page Draft Content 509135480 to Bogaerts et al 2020a

2021-02-16T11:55:24Z

Scipediacontent moved page Draft Content 509135480 to Bogaerts et al 2020a

Scipediacontent: Created page with " == Abstract == Traffic forecasting is an important research area in Intelligent Transportation Systems that is focused on anticipating traffic in order to mitigate congesti..."

2021-02-16T11:55:21Z

Created page with " == Abstract == Traffic forecasting is an important research area in Intelligent Transportation Systems that is focused on anticipating traffic in order to mitigate congesti..."

New page

== Abstract ==

Traffic forecasting is an important research area in Intelligent Transportation Systems that is focused on anticipating traffic in order to mitigate congestion. In this work we propose a deep neural network that simultaneously extracts the spatial features of traffic, using graph convolution, and its temporal features by means of Long Short Term Memory (LSTM) cells to make both short-term and long-term predictions. The model is trained and tested using sparse trajectory (GPS) data coming from the ride-hailing service of DiDi in the cities of Xi'an and Chengdu in China. Besides, presenting the deep neural network, we also propose a data-reduction technique based on temporal correlation to select the most relevant road links to be used as input. Combining the suggested approaches, our model obtains better results compared to high-performance algorithms for traffic forecasting, such as LSTM or the algorithms presented in the TRANSFOR19 forecasting competition. The model is capable of maintaining its performance over different time-horizons from 5 min to up to 4 h with multi-step predictions.

== Original document ==

The different versions of the original document can be found in:

* [https://hdl.handle.net/10067/1686650151162165141 https://hdl.handle.net/10067/1686650151162165141]

← Older revision	Revision as of 11:55, 16 February 2021
(No difference)

Bogaerts et al 2020a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 509135480 to Bogaerts et al 2020a

Scipediacontent: Created page with " == Abstract == Traffic forecasting is an important research area in Intelligent Transportation Systems that is focused on anticipating traffic in order to mitigate congesti..."