Open Access
MATEC Web Conf.
Volume 195, 2018
The 4th International Conference on Rehabilitation and Maintenance in Civil Engineering (ICRMCE 2018)
Article Number 04017
Number of page(s) 10
Section Transportation Engineering
Published online 22 August 2018
  1. United Nations, Department of Economic and Social Affairs, World Urbanization Prospects: The 2014 Revision, Highlights (ST/ESA/SER.A/352) (2014) [Google Scholar]
  2. OECD, Managing Urban Traffic Congestion, Organisation for Economic Development, Paris, (2007) [Google Scholar]
  3. J.L. Bowman, M.E. Ben-Akiva, Activity-based disaggregate travel demand model system with activity schedules. Transp. Res. A 35, 1-28 (2001) [CrossRef] [Google Scholar]
  4. J.A. Carrasco, E.J. Miller, Exploring the propensity to perform social activities: a social network approach. Transportation 33(5), 463-480 (2006) [CrossRef] [Google Scholar]
  5. H.J. Timmermans, J. Zhang, Modeling household activity travel behavior: examples of state of the art modeling approaches and research agenda. Transp. Res. B 43(2), 187-190 (2009) [CrossRef] [Google Scholar]
  6. K. Manaugh, A.M. El-Geneidy, What makes travel ‘local’ : Defining and understanding local travel behavior. The Journal of Transport and Land Use, 5 (3), pp. 15-27, doi: 10.5198/jtlu.v5i3.300 (2012) [Google Scholar]
  7. D. Salon, E.M. Aligula, Urban travel in Nairobi, Kenya: analysis, insights, and opportunities. Journal of Transport Geography, 22, pp. 65-76 (2012) [CrossRef] [Google Scholar]
  8. M. Saberi, H.S. Mahmassani, D. Brockmann, A. Hosseini, A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin-destination demand networks. Transportation. Springer Science and Business Media. New York. DOI 10.1007/s11116-016-9706-6 (2016) [Google Scholar]
  9. Y. Chen, A. Frei, H.S. Mahmassani, Exploring activity and destination choice behavior in social networking data. Proceedings of the transportation research board 94th annual meeting (No. 15-5808), Washington (2015) [Google Scholar]
  10. C. Daganzo, Urban gridlock: macroscopic modeling and mitigation approaches. Transp. Res. B 41(1), 49-62 (2007) [CrossRef] [Google Scholar]
  11. N. Geroliminis, C. Daganzo, Existence of urban-scale macroscopic fundamental diagrams: some experimental findings. Transp. Res. B 45(3), 605-617 (2008) [CrossRef] [Google Scholar]
  12. H. Mahmassani, M. Saberi, A. Zockaie, Urban network gridlock: theory, characteristics, and dynamics. Trans. Res. C 36, 480-497 (2013) [CrossRef] [Google Scholar]
  13. M. Saberi, H. Mahmassani, T. Hou, A. Zockaie, Estimating network fundamental diagram using threedimensional vehicle trajectories: extending Edie’s definitions of traffic flow variables to networks. Transp. Res. Rec. 2422, 12-20 (2014) [CrossRef] [Google Scholar]
  14. J.W. Joubert, K. Axhausen, A complex network approach to understand commercial vehicle movement. Transportation 40(3), 729-750 (2013) [CrossRef] [Google Scholar]
  15. J. Kim, H.S. Mahmassani, Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories. Trans. Res. C 59, 375-390 (2015) [CrossRef] [Google Scholar]
  16. M.G. McNally, The Four Step Model, to appear as Chapter 3 in Hensher and Button (eds). “Handbook of Transport Modelling”, Pergamonn 2nd Ed (2007). [Google Scholar]
  17. Department of Transport, Republic of Indonesia, Origin-Destination Matrix of Bali Province. Jakarta (2016) [Google Scholar]
  18. Bureau of Statistic of Bali Province, Bali in Figure 2015, Denpasar, Bali (2016) [Google Scholar]
  19. Department of Public Work, The average daily traffic (ADT) of national road in Bali Province. Jakarta (2016) [Google Scholar]

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.