Inferring Passenger Travel Demand to Improve Urban Mobility in Developing Countries Using Cell Phone Data: A Case Study of Senegal
暂无分享,去创建一个
Francisco Antunes | Santi Phithakkitnukoon | Carlos Bento | Rui Gomes | Titipat Sukhvibul | Merkebe Getachew Demissie | S. Phithakkitnukoon | C. Bento | Francisco Antunes | Titipat Sukhvibul | Rui Gomes | M. Demissie
[1] Victor Soto,et al. Robust Land Use Characterization of Urban Landscapes using Cell Phone Data , 2011 .
[2] Paul Mullen,et al. Estimating the demand for urban bus travel , 1975 .
[3] Wei Wang,et al. Bus Passenger Origin-Destination Estimation and Related Analyses , 2011 .
[4] Carlos Bento,et al. Analysis of the pattern and intensity of urban activities through aggregate cellphone usage , 2015 .
[5] Hillel Bar-Gera,et al. Evaluation of a Cellular Phone-Based System for Measurements of Traffic Speeds and Travel Times: A Case Study from Israel , 2007 .
[6] Margaret Martonosi,et al. Identifying Important Places in People's Lives from Cellular Network Data , 2011, Pervasive.
[7] Gerd Kortuem,et al. Catch me if you can: Predicting mobility patterns of public transport users , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).
[8] Peter Wilkinson,et al. Hybrid urban transport systems in developing countries: Portents and prospects , 2013 .
[9] William. Agyemang. Measurement of service quality of “Trotro” as public transportation in Ghana: A case study of the city of Kumasi , 2013 .
[10] Stuart Hannabuss,et al. United Nations Population Fund (UNFPA) , 2013 .
[11] Liang Liu,et al. Estimating Origin-Destination Flows Using Mobile Phone Location Data , 2011, IEEE Pervasive Computing.
[12] Alexandre M. Bayen,et al. Evaluation of traffic data obtained via GPS-enabled mobile phones: The Mobile Century field experiment , 2009 .
[13] Balázs Csanád Csáji,et al. Exploring the Mobility of Mobile Phone Users , 2012, ArXiv.
[14] Xavier Godard. Urban Transport Reform in Dakar, Lessons from 15 Years Experience, The Search of Complementarity between Bus and Minibus Operators , 2007 .
[15] Carlos Bento,et al. Exploring cellular network handover information for urban mobility analysis , 2013 .
[16] Merkebe Getachew Demissie,et al. Combining datasets from multiple sources for urban and transportation planning: emphasis on cellular network data , 2014 .
[17] W. Hongsakham,et al. Estimating road traffic congestion from cellular handoff information using cell-based neural networks and K-means clustering , 2008, 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.
[18] Alexandre M. Bayen,et al. Understanding Road Usage Patterns in Urban Areas , 2012, Scientific Reports.
[19] Marta C. González,et al. Analyzing Cell Phone Location Data for Urban Travel , 2015 .
[20] Gerd Kortuem,et al. Mining temporal patterns of transport behaviour for predicting future transport usage , 2013, UbiComp.
[21] P. Olivier,et al. Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data , 2012, PloS one.
[22] O. Järv,et al. Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones , 2010 .
[23] Pu Wang,et al. Development of origin–destination matrices using mobile phone call data , 2014 .
[24] Carlos Bento,et al. Intelligent road traffic status detection system through cellular networks handover information: An exploratory study , 2013 .
[25] Marta C. González,et al. Origin-destination trips by purpose and time of day inferred from mobile phone data , 2015 .
[26] Joseph Ferreira,et al. Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore , 2017, IEEE Transactions on Big Data.
[27] Bus Rapid Transit Planning Guide , 2007 .
[28] Daniel K Boyle. Fixed-Route Transit Ridership Forecasting and Service Planning Methods , 2006 .
[29] Marco Luca Sbodio,et al. AllAboard: A System for Exploring Urban Mobility and Optimizing Public Transport Using Cellphone Data , 2013, ECML/PKDD.
[30] David A. Mfinanga,et al. An Evaluation of Policy Approaches to Upgrading and Integrating Paratransit in African Urban Public Transport Systems: Results of the First Round of a Delphi Survey , 2012 .
[31] Wasan Pattara-Atikom,et al. Classification of Cellular Phone Mobility using Naive Bayes Model , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.
[32] Marta C. González,et al. The path most traveled: Travel demand estimation using big data resources , 2015, Transportation Research Part C: Emerging Technologies.
[33] Marta C. González,et al. Assessing the Impact of Real-time Ridesharing on Urban Traffic using Mobile Phone Data , 2015 .
[34] Ramón Cáceres,et al. Route classification using cellular handoff patterns , 2011, UbiComp '11.
[35] Caroline O. Buckee,et al. The impact of biases in mobile phone ownership on estimates of human mobility , 2013, Journal of The Royal Society Interface.
[36] Zbigniew Smoreda,et al. D4D-Senegal: The Second Mobile Phone Data for Development Challenge , 2014, ArXiv.
[37] M. Kemp,et al. Para-Transit: Neglected Options for Urban Mobility , 1974 .
[38] Dietmar Bauer,et al. Inferring land use from mobile phone activity , 2012, UrbComp '12.
[39] Johan Wideberg,et al. Deriving origin destination data from a mobile phone network , 2007 .