Network Monitoring and Personalized Traffic Control: A Starting Point based on Experiences from the Municipality of Enschede in the Netherlands

Sander Veenstra, Tom Thomas

2011

Abstract

An increasing number of cities have severe traffic problems. We identify three main challenges for managing these problems. The first one is to achieve a proper amount of monitoring. Secondly, predictions of the effects of network wide management measures require knowledge of the underlying travel behaviour. Finally, measures should be in line with needs and expectations of travellers to be effective. In this paper we focus on these challenges. We use loop detectors near traffic lights in the Dutch city of Enschede to monitor the traffic situation in its network. We developed a method to estimate delays from these measurements. We also use a simple forecasting algorithm to predict flows and travel times for different time horizons. Regarding travel behaviour, we used a license plate survey to study route choice. We discuss how the results from these studies may be used to improve urban traffic management.

References

  1. Hasberg, P., Serwill, D.: Stadtinfoköln - a global mobility information system for the Cologne area, 7th World Congress on Intelligent Transport Systems, Turin, Italy (2000)
  2. Kellerman, A., Schmid, A.: Mobinet: Intermodal traffic management in Munich -control centre development, 7th World Congress on Intelligent Transport Systems, Turin, Italy (2000)
  3. Leitsch, B.: A Public-privat partnership for mobility - Traffic management Center Berlin, 9th World Congress on Intelligent Transport Systems, Chicago (2002)
  4. Nagatani, T.: Vehicular traffic through a sequence of green-wave lights, Physica A: Statistical Mechanics and its Applications, Vol. 380, (2007) 503-511
  5. Vrancken, J., Van Schuppen, J.H., Dos Santos Soares, M., Ottenhof, F.: A HierarchicalNetwork Model for Road Traffic Control, Proceedings of the 2009 IEEE International Conference on Networking, Sensing and Control, Okyama, Japan, (2009) 340-344
  6. Hodge, V.J., Krishnan, R., Jackson T., Austin, J., Polak, J.: Short Term Traffic Prediction Using a Binary Neural Network, 43rd Annual UTSG Conference, Open University, Milton Keynes, UK (2011)
  7. Wismans, L.J.J, Van Berkum, E.C., Bliemer, M.C.J.: Comparison of Evolutionary Multi Objective Algorithms for the Dynamic Network Design Problem. ICNSC - IEEE conference, Delft (2011)
  8. Mitsakis, E., Salanova, J.M., Giannopoulos, G.: Combined dynamic traffic assignment and urban traffic control models, Procedia - Social and Behavioral Sciences, Vol. 20, (2011) 427 - 436
  9. Wardrop, J. G.: Some theoretical aspects of road traffic research, Proceedings, Institute of Civil Engineers, PART II- 1, (1952) 325-378.
  10. Bar-Gera, H., Mirchandani, P., Fan, W.: Evaluating the assumption of independent turning probabilities, Transportation Research part B, Vol. 40, (2006) 903 - 916
  11. Chen, T.Y., Chang, H.L., Tzeng, G.H.: Using a weight-assesing model to identify route choice criteria and information effects, Transportation Research Part A, Vol. 35, (2001) 197 - 224
  12. Mahmassani, H.S., Jou, R-C.: Transferring insights into commuter behavior dynamics from laboratory experiments to field trials. Transportation Research Vol. 34A(4), (2000) 243- 260
  13. Prato, C. G., Bekhor, S.: Applying Branch-and-Bound Technique to route choice set generation. Transportation Research Record, Vol. 1985, (2006) 19-82
  14. Jan, O., Horowitz, A. J., Peng, Z. R.: Using global positioning system data to understand variations in path choice. Transportation Research Record, Vol. 1725, (2000) 37 - 44.
  15. Zhu, S., Levinson, D.: Do people use the shortest path? An empirical test of Wardrop's first principle, 4th International Symposium on Transportation Network Reliability, July Minneapolis, USA (2010)
  16. Papinski, D., Scott, D. M.: A GIS Toolkit for route choice analysis, Journal of Transport Geography, Vol. 19, (2009) 434 - 442
  17. Hamerslag R.: Investigation into factors affecting the route choice in “Rijnstreek-West” with the aid of a disaggregate logit model. Transportation, Vol. 10, (1981) 373 - 391.
  18. Bovy, P. H. L.: On modeling route choice sets in transportation networks: a synthesis, Transport Reviews, Vol. 29 (1), (2009) 43 - 68
  19. Tarnoff, P. J., Wasson, J. S, Young, S. E., Ganig, N., Bullock, D. M., Sturdevant, J. R.: The Continuing Evolution of Travel Time Data Information Collection and Processing, Transportation Research Board Annual Meeting, Paper ID: 09-2030 (2009)
  20. Mak, W. K., Viti, F., Hoogendoorn, S. P., Hegyi, A.: Online travel time estimation in urban areas using the occupancy of long loop detectors, 12th IFAC symposium on transportation systems, Redondo Beach (2009)
  21. Wild, D.: Short-term forecasting based on a transformation and classification of traffic volume time series, International Journal of Forecasting, Vol. 13, (1997) 63 - 72
  22. Van Grol, R., Inaudi, D., Kroes, E.: On-line traffic condition forecasting using on-line measurements and a historical database, 7th World Congress on Intelligent Transport Systems, Turin, Italy (2000)
  23. Dia, H.: An object-oriented neural network approach to short-term traffic forecasting,” European Journal of Operational Research, Vol. 131, (2001) 253 - 261
  24. Yin, H., Wong, S. C., Xu, J., Wong, C. K.: Urban traffic flow prediction using a fuzzyneural approach, Transportation Research Part C, Vol. 10, (2002) 85 - 98
  25. Chung E.: Classification of traffic pattern, 10th World Congress on Intelligent Transport Systems, Madrid (2003)
  26. Weijermars, W. A. M,: Analysis of urban traffic patterns using clustering, Ph.D. Thesis, University of Twente, Enschede, The Netherlands (2007)
  27. Thomas, T., Weijermars, W. A. M, Van Berkum E.C.: Predictions of Urban Volumes in Single Time Series, IEEE Transactions on Intelligent Transportation Systems, Vol. 11 (1), (2010) 71 - 80
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Paper Citation


in Harvard Style

Thomas T. and Veenstra S. (2011). Network Monitoring and Personalized Traffic Control: A Starting Point based on Experiences from the Municipality of Enschede in the Netherlands . In Proceedings of the 1st International Workshop on Future Internet Applications for Traffic Surveillance and Management - Volume 1: FIATS-M, ISBN 978-989-8425-87-4, pages 67-82. DOI: 10.5220/0004473200670082


in Bibtex Style

@conference{fiats-m11,
author={Tom Thomas and Sander Veenstra},
title={Network Monitoring and Personalized Traffic Control: A Starting Point based on Experiences from the Municipality of Enschede in the Netherlands},
booktitle={Proceedings of the 1st International Workshop on Future Internet Applications for Traffic Surveillance and Management - Volume 1: FIATS-M,},
year={2011},
pages={67-82},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004473200670082},
isbn={978-989-8425-87-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Future Internet Applications for Traffic Surveillance and Management - Volume 1: FIATS-M,
TI - Network Monitoring and Personalized Traffic Control: A Starting Point based on Experiences from the Municipality of Enschede in the Netherlands
SN - 978-989-8425-87-4
AU - Thomas T.
AU - Veenstra S.
PY - 2011
SP - 67
EP - 82
DO - 10.5220/0004473200670082