Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1109/ITSC.2016.7795925guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
research-article

Reconstruction of public transport state

Published: 01 November 2016 Publication History

Abstract

Interest towards the applications of ICT in public and private urban transport has grown significantly over the last few years. In the field of the user interfaces with transportation, however, continuous, highly context-aware, real time interaction can still be found only in a very limited number of cases, mostly in private transportation. One of the main issues in actually developing an assistive, portable, continuously interacting application is getting to know the transports system state (equations of motion of the means, position of the users on the means). In most cities the most temporally accurate data available is the estimated departure time of the next train or bus at the stops.

References

[1]
Balakrishnan, V. K., Graph Theory, McGraw-Hill, 1997
[2]
Ekkehard Khler, Katharina Langkau, Martin Skutella, Time-Expanded Graphs for Flow-Dependent Transit Times, 2002
[3]
R. E. Kalman, A New Approach to Linear Filtering and Prediction Problems, Transaction of the ASME, Journal of Basic Engineering pp. 35–45, March 1960
[4]
S. Thrun, W. Burgard, D. Fox, Probabilistic Robotics pp. 48–54, 2005
[5]
Handte, Marcus and Foell, Stefan and Wagner, Stephan and Kortuem, An Internet-of-Things Enabled Connected Navigation System for Urban Bus Riders, Gerd and Marron, Pedro, IEEE
[6]
E. A. Wan, R. Van der Merwe, The Unscented Kalman Filter for Nonlinear Estimation, Oregon Graduate Institute of Science and Technology, 2000
[7]
Steven I-Jy Chien, Chandra Mouly Kuchipudi, Dynamic Travel Time Prediction with Real-Time and Historic Data
[8]
Huifang Feng, Chunfeng Liu, Yantai Shu, Oliver W. W. Yang, Location Prediction of Vehicles in VANETs Using A Kalman Filter
[9]
M. Deeshma, Ashish Verma, Travel, time modeling for bus transport system in Bangalore city
[10]
J.W. Grotenhuis, B. Wiegmans, P. Rietveld, The desired quality of integrated multimodal travel information in public transport: Customer needs for time and effort savings, Transport Policy, 2007
[11]
U. Carrascal, A Review of Travel Time Estimation and Forecasting for Advanced Traveler Information Systems, M.S. thesis, Universidad del Pais Vasco, Leioa, Spain, 2012.
[12]
L. Moreira-Matias and J. Mendes-Moreira and J. F. de Sousa and J. Gama, Improving Mass Transit Operations by Using AVL-Based Systems: A Survey, IEEE Transactions on Intelligent Transportation System
[13]
J. Hine, J. Scott, Seamless, accessible travel: users? views of the public transport journey and interchange, Transport Policy 7: 217–226, 2000
[14]
Caspar G., Chorus Eric, J. E. Molin, Bert Van Wee, Use and Effects of Advanced Traveller Information Services (ATIS): A Review of the Literature, Transport Reviews, 2006

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)
2678 pages

Publisher

IEEE Press

Publication History

Published: 01 November 2016

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 01 Sep 2024

Other Metrics

Citations

View Options

View options

Get Access

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media