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Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study

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Cited by:

  1. Wang, Zhaohan & Ramezani, Mohsen & Levinson, David, 2024. "How mandatory are ‘Mandatory’ lane changes? An analytical and experimental study on the costs of missing freeway exits," Transportation Research Part B: Methodological, Elsevier, vol. 186(C).
  2. Hahnel, Ulf J.J. & Gölz, Sebastian & Spada, Hans, 2013. "How accurate are drivers’ predictions of their own mobility? Accounting for psychological factors in the development of intelligent charging technology for electric vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 48(C), pages 123-131.
  3. Calastri, Chiara & Hess, Stephane & Choudhury, Charisma & Daly, Andrew & Gabrielli, Lorenzo, 2019. "Mode choice with latent availability and consideration: Theory and a case study," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 374-385.
  4. Bulu, Melih, 2014. "Upgrading a city via technology," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 63-67.
  5. Toşa, Cristian & Sato, Hitomi & Morikawa, Takayuki & Miwa, Tomio, 2018. "Commuting behavior in emerging urban areas: Findings of a revealed-preferences and stated-intentions survey in Cluj-Napoca, Romania," Journal of Transport Geography, Elsevier, vol. 68(C), pages 78-93.
  6. Firnkorn, Jörg, 2012. "Triangulation of two methods measuring the impacts of a free-floating carsharing system in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1654-1672.
  7. Xiaofeng Lou & Changhai Peng, 2022. "Planning of a comprehensive transportation system in Ma’anshan based on mobile phone signaling data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(7), pages 9380-9406, July.
  8. Shen, Yue & Kwan, Mei-Po & Chai, Yanwei, 2013. "Investigating commuting flexibility with GPS data and 3D geovisualization: a case study of Beijing, China," Journal of Transport Geography, Elsevier, vol. 32(C), pages 1-11.
  9. Bwambale, Andrew & Choudhury, Charisma F. & Hess, Stephane, 2019. "Modelling departure time choice using mobile phone data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 424-439.
  10. Iago C. Cavalcante & Rodolfo I. Meneguette & Renato H. Torres & Leandro Y. Mano & Vinícius P. Gonçalves & Jó Ueyama & Gustavo Pessin & Georges D. Amvame Nze & Geraldo P. Rocha Filho, 2022. "Federated System for Transport Mode Detection," Energies, MDPI, vol. 15(23), pages 1-17, December.
  11. Wenbo Zhang & Satish V. Ukkusuri & Jian John Lu, 2017. "Impacts of urban built environment on empty taxi trips using limited geolocation data," Transportation, Springer, vol. 44(6), pages 1445-1473, November.
  12. Roy, Avipsa & Fuller, Daniel & Nelson, Trisalyn & Kedron, Peter, 2022. "Assessing the role of geographic context in transportation mode detection from GPS data," Journal of Transport Geography, Elsevier, vol. 100(C).
  13. Satomi Kimijima & Masahiko Nagai, 2017. "Human Mobility Analysis for Extracting Local Interactions under Rapid Socio-Economic Transformation in Dawei, Myanmar," Sustainability, MDPI, vol. 9(9), pages 1-14, September.
  14. Muhammad Shafique & Eiji Hato, 2015. "Use of acceleration data for transportation mode prediction," Transportation, Springer, vol. 42(1), pages 163-188, January.
  15. Rola Y. M. Mohammed, 2021. "Optimizing Temporal Business Opportunities," International Journal of Business and Management, Canadian Center of Science and Education, vol. 15(11), pages 104-104, July.
  16. Yi Zhu, 2022. "Inference of activity patterns from urban sensing data using conditional random fields," Environment and Planning B, , vol. 49(2), pages 549-565, February.
  17. Hong, Ye & Stüdeli, Emanuel & Raubal, Martin, 2023. "Evaluating geospatial context information for travel mode detection," Journal of Transport Geography, Elsevier, vol. 113(C).
  18. Xiaofang Yang & Hai Jiang, 2020. "Influence of Electronic-Docking Stations on China’s Dockless Bikesharing Programs: Evidence from Beijing," Sustainability, MDPI, vol. 12(9), pages 1-20, April.
  19. Peter Widhalm & Yingxiang Yang & Michael Ulm & Shounak Athavale & Marta González, 2015. "Discovering urban activity patterns in cell phone data," Transportation, Springer, vol. 42(4), pages 597-623, July.
  20. Jingqiu Guo & Yangzexi Liu & Lanfang Zhang & Yibing Wang, 2018. "Driving Behaviour Style Study with a Hybrid Deep Learning Framework Based on GPS Data," Sustainability, MDPI, vol. 10(7), pages 1-16, July.
  21. Wenyun Tang & David Levinson, 2014. "An empirical study of the deviation between actual and shortest travel time paths," Working Papers 000125, University of Minnesota: Nexus Research Group.
  22. Mariem Fekih & Tom Bellemans & Zbigniew Smoreda & Patrick Bonnel & Angelo Furno & Stéphane Galland, 2021. "A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)," Transportation, Springer, vol. 48(4), pages 1671-1702, August.
  23. Danielle McCool & Peter Lugtig & Barry Schouten, 2024. "Maximum interpolable gap length in missing smartphone-based GPS mobility data," Transportation, Springer, vol. 51(1), pages 297-327, February.
  24. Yijing Lu & Lei Zhang, 2015. "Imputing trip purposes for long-distance travel," Transportation, Springer, vol. 42(4), pages 581-595, July.
  25. Siripirote, Treerapot & Sumalee, Agachai & Ho, H.W., 2020. "Statistical estimation of freight activity analytics from Global Positioning System data of trucks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
  26. Reinau, Kristian Hegner & Harder, Henrik & Weber, Michael, 2015. "The SMS–GPS-Trip method: A new method for collecting trip information in travel behavior research," Telecommunications Policy, Elsevier, vol. 39(3), pages 363-373.
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