AN EFFICIENT ALGORITHM TO ESTIMATE REAL-TIME TRAFFIC INFORMATION BASED ON MULTIPLE DATA SOURCES

Du Bowen, Liang Yun, Ma Dianfu, Lv Weifeng, Zhu Tongyu

Abstract

Gathering traffic congestion information from all available sources to provide real-time traffic information not only makes reliable traffic predictions for management center, but also supports travelers to help guiding their transit decision. However, the key issue is that the quality of existing multiple traffic data sources are uncertain, and how to use them for performing trusty travel time estimation is a question. In this paper, a novel algorithm is proposed to address this problem. Firstly, through analyzing large amounts of traffic data, the reliability of evidence and its relationship with road network are defined in spatio-temporal dimension. Secondly, after using an improved aggregation method based on Dempster-Shafer evidence theory, the optimized evidences are adopted to estimate each link’s average link travel time. Comparative experiments of the real test-vehicle scheduling signals and real-time system data (supported by some 15000 floating cars and 320 loop detectors) indicate that the new algorithm is proved to be both reasonable and practical. It can be applied in real-time systems to manage large amount of data.

References

  1. Aomori, N. K. (1999). Prefectural travel time system by using vehicle information and communicationsystem (vics). In International Conference of Intelligent Transportation Systems.
  2. Corrado de Fabritiis, Roberto Ragona, G. V. (2008). Traffic estimation and prediction based on real time floating car data. In he 11th International IEEE Conference on Intelligent Transportation Systems, Beijing, China.
  3. Petty, K. F. (1998). Accurate estimation of travel times from single-loop detectors. Transportation Research Part A: Policy and Practice.
  4. Pushkar A, F.L. Hall, J. A.-D. (1994). Estimation of speeds from single-loop freeway flow and occupancy data using cusp catastrophe theory model. Transportation Research Record.
  5. Qing-jie Kong, Y. C. and Liu, Y. (2007). An improved evidential fusion approach for real-time urban link speed estimation. In IEEE Intelligent Transportation Systems Conference Seattle, WA, USA.
  6. Wang, Y.-M. (2005). Computers and operations research. In A preference aggregation method through the estimation of utility.
Download


Paper Citation


in Harvard Style

Bowen D., Yun L., Dianfu M., Weifeng L. and Tongyu Z. (2010). AN EFFICIENT ALGORITHM TO ESTIMATE REAL-TIME TRAFFIC INFORMATION BASED ON MULTIPLE DATA SOURCES . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 507-510. DOI: 10.5220/0002705405070510


in Bibtex Style

@conference{icaart10,
author={Du Bowen and Liang Yun and Ma Dianfu and Lv Weifeng and Zhu Tongyu},
title={AN EFFICIENT ALGORITHM TO ESTIMATE REAL-TIME TRAFFIC INFORMATION BASED ON MULTIPLE DATA SOURCES},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={507-510},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002705405070510},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - AN EFFICIENT ALGORITHM TO ESTIMATE REAL-TIME TRAFFIC INFORMATION BASED ON MULTIPLE DATA SOURCES
SN - 978-989-674-021-4
AU - Bowen D.
AU - Yun L.
AU - Dianfu M.
AU - Weifeng L.
AU - Tongyu Z.
PY - 2010
SP - 507
EP - 510
DO - 10.5220/0002705405070510