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Travel Time Estimation in the Age of Big Data
2 references·9 citing·52 second hop
Travel Time Estimation in the Age of Big Data (2019)Travel Time Estimation in the Age of Big …A Mean-Risk Model for the Traffic Assignment Problem with Stochastic Travel Times (2014)A Mean-Risk Model for the Tra…A probabilistic multipath traffic assignment model which obviates path enumeration (1971)A probabilistic multipath tra…Reliable route planning and time savings in real-world urban intermodal transportation networks: Evidence from Hamburg, Germany (2023)Reliable route planning and t…A Method Using Inverse Shortest Paths Problem to Estimate Stopover Tourist Destinations Based on Heterogeneity (2022)A Method Using Inverse Shorte…Emergency response facility location in transportation networks: A literature review (2021)Emergency response facility l…A Survey on the Advancement of Travel Time Estimation Using Mobile Phone Network Data (2021)A Survey on the Advancement o…Data-driven network loading (2020)Data-driven network loadingA review of systematic evaluation and improvement in the big data environment (2020)A review of systematic evalua…“Make no little plans”: Impactful research to solve the next generation of transportation problems (2020)“Make no little plans”: Impac…Ridesourcing systems: A framework and review (2019)Ridesourcing systems: A frame…Data-driven urban management: Mapping the landscape (2019)Data-driven urban management:…CAPACITY RESTRAINT IN ASSIGNMENT PROGRAMS (1961)Capacity restraint in multi-travel mode assignment programs (1962)Traffic assignment problem for a general network (1969)On Stochastic Models of Traffic Assignment (1977)On the Formation of Travel Demand Models and Economic Evaluation Measures of User Benefit (1977)Discrete Choice Methods and their Applications to Short Term Travel Decisions (1999)Platform Competition in Two-Sided Markets (2003)The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms (2003)Competition in two-sided markets (2006)Optimizing matching time interval and matching radius in on-demand ride-sourcing markets (2019)Fifty years of the bottleneck model: A bibliometric review and future research directions (2020)Pricing and equilibrium in on-demand ride-pooling markets (2020)The Social Logic of Space (1984)Airbnb: disruptive innovation and the rise of an informal tourism accommodation sector (2013)Disruptive Change in the Taxi Business: The Case of Uber (2016)Data-intensive applications, challenges, techniques and technologies: A survey on Big Data (2014)How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study (2015)Critical analysis of Big Data challenges and analytical methods (2016)Big data, technology capability and construction project quality: a cross-level investigation (2020)Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students (2022)Identification of accident-injury type and bodypart factors from construction accident reports: A graph-based deep learning framework (2022)Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future (2014)Where is the land of Opportunity? 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this work references cited by second hop

References

  • 1971A probabilistic multipath traffic assignment model which obviates path enumeration856 cited
  • 2014A Mean-Risk Model for the Traffic Assignment Problem with Stochastic Travel Times77 cited

Cited by

  • 2019Ridesourcing systems: A framework and review549 cited
  • 2019Data-driven urban management: Mapping the landscape217 cited
  • 2021Emergency response facility location in transportation networks: A literature review71 cited
  • 2020A review of systematic evaluation and improvement in the big data environment40 cited
  • 2020“Make no little plans”: Impactful research to solve the next generation of transportation problems29 cited
  • 2021A Survey on the Advancement of Travel Time Estimation Using Mobile Phone Network Data11 cited
  • 2023Reliable route planning and time savings in real-world urban intermodal transportation networks: Evidence from Hamburg, Germany10 cited
  • 2020Data-driven network loading7 cited
  • 2022A Method Using Inverse Shortest Paths Problem to Estimate Stopover Tourist Destinations Based on Heterogeneity3 cited

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