Open Access
MATEC Web Conf.
Volume 81, 2016
2016 5th International Conference on Transportation and Traffic Engineering (ICTTE 2016)
Article Number 03006
Number of page(s) 7
Section Traffic Control
Published online 25 October 2016
  1. M. Birdsall, Google and ITE: The road ahead for self-driving cars, ITE Journal 84, 5, pp. 36–39 (2014)
  2. N. Navet, Y. Song, F. Simonot-Lion, C. Wilwert, Trends in automotive communication systems, Proc. of the IEEE 93, no. 6, pp. 1204–1223 (2005) [CrossRef]
  3. M. Selinger, L. Schmidt, Adaptive traffic control systems in the U.S.: Updated summary and comparison, HDR Engineering, Tech. Rep. (2010)
  4. H. Prothmann, Organic Traffic Control. KIT Scientific Publishing (2011)
  5. A. Stevanovic, National Research Council (U.S.), Adaptive traffic control systems: domestic and foreign state of practice, Synthesis of highway practice (2010) [CrossRef]
  6. N. H. Gartner, OPAC Strategy for demand-responsive decentralized traffic signal control, in Control, Comp., Communic. in Transp. (1989)
  7. A. G. Sims, K. W. Dobinson, The Sydney coordinated adaptive traffic (SCAT) system – Philosophy and benefits, IEEE Trans. Veh. Techn. 29, 130–137 (1980) [CrossRef]
  8. D. I. Robertson, R. D. Bretherton, Optimizing networks of traffic signals in real time – the SCOOT method, IEEE Trans. Veh. Technol. 40, 11–15 (1991) [CrossRef]
  9. R. Chrobok, O. Kaumann, J. Wahle, M. Schreckenberg, Different methods of traffic forecast based on real data, European Journal of Operational Research 155, 3, pp. 558–568 (2004) [CrossRef]
  10. S. Garside, K. Lindveld, and J. Whittaker, Tracking and predicting a network traffic process. Intern. Journal of Forecasting 13, pp. 51–61 (1997) [CrossRef]
  11. M. S. Dougherty, M. R. Cobbett, Short-term inter-urban traffic forecasts using neural networks, Intern. Journal of Forecasting 13, 1, pp. 21–31 (1997) [CrossRef]
  12. R. Adhikari, R. K. Agrawal, Performance evaluation of weights selection schemes for linear combination of multiple forecasts, Artif. Intell. Rev., 529–548 (2014) [CrossRef]
  13. M. Sommer, S. Tomforde, J. Hähner, D. Auer, Learning a Dynamic Re-combination Strategy of Forecast Techniques at Runtime, Proc. of IEEE Int. Conf. Autonomic Computing, pp. 261–266 (2015)
  14. M. C. Bell, R. D. Bretherton, Ageing of fixed-time traffic signal plans, 2nd Int. Conf. On Road Traffic Control, pp. 77–80 (1986)
  15. J. Barcelo, J. Casas, Dynamic network simulation with AIMSUN, Int. Symp. on Transp. Simulation. Kluwer, pp. 1–25 (2002)
  16. R. J. Hyndman, Y. Khandakar, Automatic time series forecasting: the forecast package for R, J. Statistical Software 26, 3, pp. 1–22 (2008)
  17. L. I. Panis, S. Broekx, R. Liu, Modelling instantaneous traffic emission and the influence of traffic speed limits, Science of The Total Environment 371, pp. 270–285 (2006) [CrossRef]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.