Table of Contents Author Guidelines Submit a Manuscript
Journal of Advanced Transportation
Volume 2017, Article ID 2697678, 10 pages
https://doi.org/10.1155/2017/2697678
Research Article

The Effect of Connected Vehicle Environment on Global Travel Efficiency and Its Optimal Penetration Rate

School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, Beihang University, Beijing 100191, China

Correspondence should be addressed to Chuan Ding; nc.ude.aaub@gnidc

Received 17 February 2017; Accepted 30 May 2017; Published 6 July 2017

Academic Editor: Xiaopeng Li

Copyright © 2017 Rongjian Dai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Nourinejad and M. J. Roorda, “Impact of hourly parking pricing on travel demand,” Transportation Research Part A: Policy and Practice, vol. 98, pp. 28–45, 2017. View at Publisher · View at Google Scholar
  2. C. Ding, Y. Lin, and C. Liu, “Exploring the influence of built environment on tour-based commuter mode choice: a cross-classified multilevel modeling approach,” Transportation Research Part D: Transport and Environment, vol. 32, pp. 230–238, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. C. Ding, D. Wang, C. Liu, Y. Zhang, and J. Yang, “Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance,” Transportation Research Part A: Policy and Practice, vol. 100, pp. 65–80, 2017. View at Publisher · View at Google Scholar
  4. X. Ma, Y. J. Wu, Y. Wang, F. Chen, and J. Liu, “Mining smart card data for transit riders' travel patterns,” Transportation Research Part C: Emerging Technologies, vol. 36, pp. 1–12, 2013. View at Publisher · View at Google Scholar · View at Scopus
  5. X. Ma, C. Liu, H. Wen, Y. Wang, and Y. Wu, “Understanding commuting patterns using transit smart card data,” Journal of Transport Geography, vol. 58, pp. 135–145, 2017. View at Publisher · View at Google Scholar
  6. J. Enrique Fernández L., J. de Cea Ch, and G. Germán Valverde, “Effect of advanced traveler information systems and road pricing in a network with non-recurrent congestion,” Transportation Research Part A: Policy and Practice, vol. 43, no. 5, pp. 481–499, 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. R. Arnott, A. de Palma, and R. Lindsey, “Does providing information to drivers reduce traffic congestion?” Transportation Research Part A: General, vol. 25, no. 5, pp. 309–318, 1991. View at Publisher · View at Google Scholar · View at Scopus
  8. A. De Palma, R. Lindsey, and N. Picard, “Aversion, the value of information, and traffic equilibrium,” Transportation Science, vol. 46, no. 1, pp. 1–26, 2012. View at Publisher · View at Google Scholar · View at Scopus
  9. S. Khoshmagham, Y. Feng, M. Zamanipour, and K. L. Head, “Travel time observation in privacy ensured connected vehicle environment using partial vehicle trajectories and extended tardity,” in Proceedings of the Transportation Research Board Annual Meeting, Washington, DC, USA, 2015.
  10. M. Gerla, E.-K. Lee, G. Pau, and U. Lee, “Internet of vehicles: from intelligent grid to autonomous cars and vehicular clouds,” in Proceedings of the IEEE World Forum on Internet of Things (WF-IoT '14), pp. 241–246, March 2014. View at Publisher · View at Google Scholar · View at Scopus
  11. F. Zhou, X. Li, and J. Ma, “Parsimonious shooting heuristic for trajectory design of connected automated traffic part I: theoretical analysis with generalized time geography,” Transportation Research Part B: Methodological, vol. 95, pp. 394–420, 2017. View at Publisher · View at Google Scholar
  12. J. Ma, X. Li, F. Zhou, J. Hu, and B. B. Park, “Parsimonious shooting heuristic for trajectory design of connected automated traffic part II: computational issues and optimization,” Transportation Research Part B: Methodological, vol. 95, pp. 421–441, 2017. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Ma, X. Li, S. Shladover et al., “Freeway Speed Harmonization,” IEEE Transactions on Intelligent Vehicles, vol. 1, no. 1, pp. 78–89, 2016. View at Publisher · View at Google Scholar
  14. C. Ding, X. Wu, G. Yu, and Y. Wang, “A gradient boosting logit model to investigate driver's stop-or-run behavior at signalized intersections using high-resolution traffic data,” Transportation Research Part C: Emerging Technologies, vol. 72, pp. 225–238, 2016. View at Publisher · View at Google Scholar · View at Scopus
  15. G. Londono and A. Lozano, “Dissuasive Queues in the Time Dependent Traffic Assignment Problem,” Procedia - Social and Behavioral Sciences, vol. 162, pp. 378–387, 2014. View at Publisher · View at Google Scholar
  16. X. Li, J. Cui, S. An, and M. Parsafard, “Stop-and-go traffic analysis: theoretical properties, environmental impacts and oscillation mitigation,” Transportation Research Part B: Methodological, vol. 70, no. 1, pp. 319–339, 2014. View at Publisher · View at Google Scholar · View at Scopus
  17. N. Lu, N. Cheng, N. Zhang, X. Shen, and J. W. Mark, “Connected vehicles: solutions and challenges,” IEEE Internet of Things Journal, vol. 1, no. 4, pp. 289–299, 2014. View at Publisher · View at Google Scholar · View at Scopus
  18. C.-Y. Chan, “Connected vehicles in a connected world,” in Proceedings of the 2011 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2011, pp. 86–89, April 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. R. Lindsey, T. Daniel, E. Gisches, and A. Rapoport, “Pre-trip information and route-choice decisions with stochastic travel conditions: Theory,” Transportation Research Part B: Methodological, vol. 67, pp. 187–207, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. E. Ben-Elia, R. Di Pace, G. N. Bifulco, and Y. Shiftan, “The impact of travel information's accuracy on route-choice,” Transportation Research Part C: Emerging Technologies, vol. 26, pp. 146–159, 2013. View at Publisher · View at Google Scholar · View at Scopus
  21. A. Popovič and A. Habjan, “Exploring the effects of information quality change in road transport operations,” Industrial Management and Data Systems, vol. 112, no. 9, pp. 1307–1325, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. S. C. Litescu, V. Viswanathan, H. Aydt, and A. Knoll, “The effect of information uncertainty in road transportation systems,” Journal of Computational Science, vol. 16, pp. 170–176, 2016. View at Publisher · View at Google Scholar · View at Scopus
  23. E. Ben-Elia and Y. Shiftan, “Which road do I take? A learning-based model of route-choice behavior with real-time information,” Transportation Research A: Policy and Practice, vol. 44, no. 4, pp. 249–264, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. D. Levinson, “The value of advanced traveler information systems for route choice,” Transportation Research Part C: Emerging Technologies, vol. 11, no. 1, pp. 75–87, 2003. View at Publisher · View at Google Scholar · View at Scopus
  25. R. Lindsey, T. Daniel, E. Gisches, and A. Rapoport, “Pre-trip information and route-choice decisions with stochastic travel conditions: Experiment,” Transportation Research Part B: Methodological, vol. 67, no. 9, pp. 187–207, 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. R. H. M. Emmerink, K. W. Axhausen, P. Nijkamp, and P. Rietveld, “Effects of information in road transport networks with recurrent congestion,” Transportation, vol. 22, no. 1, pp. 21–53, 1995. View at Publisher · View at Google Scholar · View at Scopus
  27. S. Litescu, V. Viswanathan, M. Lees, A. Knoll, and H. Aydt, “Information impact on transportation systems,” Journal of Computational Science, vol. 9, no. 4, pp. 88–93, 2015. View at Google Scholar