Scipediacontent: Scipediacontent moved page Draft Content 760889842 to Wan et al 2020a

2021-02-03T15:37:55Z

Scipediacontent moved page Draft Content 760889842 to Wan et al 2020a

Scipediacontent: Created page with " == Abstract == Modern urbanization is demanding smarter technologies to improve a variety of applications in intelligent transportation systems to relieve the increasing amo..."

2021-02-03T15:37:52Z

Created page with " == Abstract == Modern urbanization is demanding smarter technologies to improve a variety of applications in intelligent transportation systems to relieve the increasing amo..."

New page

== Abstract ==

Modern urbanization is demanding smarter technologies to improve a variety of applications in intelligent transportation systems to relieve the increasing amount of vehicular traffic congestion and incidents. Existing incident detection techniques are limited to the use of sensors in the transportation network and hang on human-inputs. Despite of its data abundance, social media is not well-exploited in such context. In this paper, we develop an automated traffic alert system based on Natural Language Processing (NLP) that filters this flood of information and extract important traffic-related bullets. To this end, we employ the fine-tuning Bidirectional Encoder Representations from Transformers (BERT) language embedding model to filter the related traffic information from social media. Then, we apply a question-answering model to extract necessary information characterizing the report event such as its exact location, occurrence time, and nature of the events. We demonstrate the adopted NLP approaches outperform other existing approach and, after effectively training them, we focus on real-world situation and show how the developed approach can, in real-time, extract traffic-related information and automatically convert them into alerts for navigation assistance applications such as navigation apps.

Comment: This paper is accepted for publication in IEEE Technology Engineering Management Society International Conference (TEMSCON'20), Metro Detroit, Michigan (USA)

== Original document ==

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

* [http://arxiv.org/abs/2004.13823 http://arxiv.org/abs/2004.13823]

* [http://arxiv.org/pdf/2004.13823 http://arxiv.org/pdf/2004.13823]

* [http://xplorestaging.ieee.org/ielx7/9137411/9140073/09140144.pdf?arnumber=9140144 http://xplorestaging.ieee.org/ielx7/9137411/9140073/09140144.pdf?arnumber=9140144],
: [http://dx.doi.org/10.1109/temscon47658.2020.9140144 http://dx.doi.org/10.1109/temscon47658.2020.9140144]

* [https://dblp.uni-trier.de/db/journals/corr/corr2004.html#abs-2004-13823 https://dblp.uni-trier.de/db/journals/corr/corr2004.html#abs-2004-13823],
: [https://ui.adsabs.harvard.edu/abs/2020arXiv200413823W/abstract https://ui.adsabs.harvard.edu/abs/2020arXiv200413823W/abstract],
: [https://academic.microsoft.com/#/detail/3042881534 https://academic.microsoft.com/#/detail/3042881534]

← Older revision	Revision as of 15:37, 3 February 2021
(No difference)

Wan et al 2020a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 760889842 to Wan et al 2020a

Scipediacontent: Created page with " == Abstract == Modern urbanization is demanding smarter technologies to improve a variety of applications in intelligent transportation systems to relieve the increasing amo..."