Granular quantifying traffic states using mobile probes

Quang Tran Minh, Eiji Kamioka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)


This paper proposes a novel method for detecting traffic congestions, qualifying and quantifying congestion levels using mobile phones as traffic probes. The system provides a robust mechanism for granularly comparing the seriousness of different congested areas. Congested areas are detected in a detailed manner by which exact congested positions are reported. Moreover, congestions can be detected even though no complete traffic trace due to the traffic jam is collected. This feature is quite different from, and makes the system more robust compared to the previous ones. This project also consists of a reasonable vehicle classification method based on only GPS data. This mechanism improves not only the effectiveness and the accuracy but also the scalability, thus the system is flexibly applicable for any traffic system structure, especially in developing countries where a lot of motorbikes are travelling on the roads. The evaluation reveals that the proposed ideas are novel which are not discussed in the existing work.

Original languageEnglish
Title of host publication2010 IEEE 72nd Vehicular Technology Conference Fall, VTC2010-Fall - Proceedings
Publication statusPublished - 2010
Event2010 IEEE 72nd Vehicular Technology Conference Fall, VTC2010-Fall - Ottawa, ON, Canada
Duration: 2010 Sept 62010 Sept 9

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252


Conference2010 IEEE 72nd Vehicular Technology Conference Fall, VTC2010-Fall
CityOttawa, ON


  • GPS
  • Mobile phone probes
  • Quantifying traffic state
  • Real-time traffic data
  • Traffic estimation
  • Vehicle classification

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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