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A forward Markov model for predicting bicycle speed
16 references·4 citing·47 second hop
A forward Markov model for predicting bicycle speed (2019)A forward Markov model for predicting bic…Speed, travel time and delay for intersections and road segments in the Montreal network using cyclist Smartphone GPS data (2017)Speed, travel time and delay …Empirical speed models for cycling in the Oslo road network (2017)Empirical speed models for cy…Travel mode detection based on GPS track data and Bayesian networks (2015)Travel mode detection based o…Big Data and Cycling (2015)Big Data and CyclingAn Analysis of Bicycle Travel Speed and Disturbances on Off-street and On-street Facilities (2015)An Analysis of Bicycle Travel…A quantum utility model for route choice in transport systems (2015)A quantum utility model for r…Review of GPS Travel Survey and GPS Data-Processing Methods (2014)Review of GPS Travel Survey a…Supporting large-scale travel surveys with smartphones – A practical approach (2013)Supporting large-scale travel…Random and fuzzy utility models for road route choice (2011)Random and fuzzy utility mode…A GPS-based bicycle route choice model for San Francisco, California (2011)A GPS-based bicycle route cho…Design speeds and acceleration characteristics of bicycle traffic for use in planning, design and appraisal (2010)Design speeds and acceleratio…Automating mode detection for travel behaviour analysis by using global positioning systems-enabled mobile phones and neural networks (2010)Automating mode detection for…Predicting Bicycle Travel Speeds Along Different Facilities Using GPS Data: A Proof-of-Concept Model (2007)Predicting Bicycle Travel Spe…Gaussian Markov Random Fields: Theory and Applications (2005)Gaussian Markov Random Fields…Gaussian Markov Random Fields (2005)Gaussian Markov Random FieldsRandom utility models with implicit availability/perception of choice alternatives for the simulation of travel demand (2001)Random utility models with im…Identification and investigation of cruising speeds from cycling GPS data (2025)Identification and investigat…Cycling speed profiles from GPS data: Insights for conventional and electrified bicycles in Switzerland (2025)Cycling speed profiles from G…Predicting Cyclist Speed in Urban Contexts: A Neural Network Approach (2024)Predicting Cyclist Speed in U…Improving GIS-based models for bicycling speed estimations (2019)Improving GIS-based models fo…Nonresponse Rates and Nonresponse Bias in Household Surveys (2006)Learning and inferring transportation routines (2007)Understanding mobility based on GPS data (2008)Smartphone GPS tracking—Inexpensive and efficient data collection on recreational movement (2016)Estimating city-level travel patterns using street imagery: A case study of using Google Street View in Britain (2018)Modeling real-time human mobility based on mobile phone and transportation data fusion (2018)Discrete Choice Methods and their Applications to Short Term Travel Decisions (1999)Transportation Research Board (2014)Discovering urban activity patterns in cell phone data (2015)Do People Use the Shortest Path? 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(1999)Travel Mode Detection Based on GPS Raw Data Collected by Smartphones: A Systematic Review of the Existing Methodologies (2016)Travel Mode Detection Using GPS Data and Socioeconomic Attributes Based on a Random Forest Classifier (2017)Inferring fine-grained transport modes from mobile phone cellular signaling data (2019)Bike-sharing: History, Impacts, Models of Provision, and Future (2009)Big data: The next frontier for innovation, competition, and productivity (2011)The big challenges of big data (2013)Cycling as transport (2015)Using crowdsourced data to monitor change in spatial patterns of bicycle ridership (2018)Exploring the relationship between bike-sharing and public transport in Poznań, Poland (2021)Conditional logit analysis of qualitative choice behavior (1972)A Survey of Digital Map Processing Techniques (2014)Smartphones as an integrated platform for monitoring driver behaviour: The role of sensor fusion and connectivity (2018)Transportation mode identification with GPS trajectory data and GIS information (2021)A century of trends in adult human height (2016)An intuitive Bayesian spatial model for disease mapping that accounts for scaling (2016)Spatial modeling with R‐INLA: A review (2018)Gaussian Predictive Process Models for Large Spatial Data Sets (2008)Spatial and spatio-temporal models with R-INLA (2013)
this work references cited by second hop

References

  • 2005Gaussian Markov Random Fields1,826 cited
  • 2005Gaussian Markov Random Fields: Theory and Applications1,219 cited
  • 2011A GPS-based bicycle route choice model for San Francisco, California399 cited
  • 2014Review of GPS Travel Survey and GPS Data-Processing Methods350 cited
  • 2001Random utility models with implicit availability/perception of choice alternatives for the simulation of travel demand208 cited
  • 2015Big Data and Cycling160 cited
  • 2013Supporting large-scale travel surveys with smartphones – A practical approach154 cited
  • 2015Travel mode detection based on GPS track data and Bayesian networks154 cited
  • 2010Design speeds and acceleration characteristics of bicycle traffic for use in planning, design and appraisal151 cited
  • 2010Automating mode detection for travel behaviour analysis by using global positioning systems-enabled mobile phones and neural networks136 cited
  • 2015An Analysis of Bicycle Travel Speed and Disturbances on Off-street and On-street Facilities78 cited
  • 2017Speed, travel time and delay for intersections and road segments in the Montreal network using cyclist Smartphone GPS data74 cited
  • 2011Random and fuzzy utility models for road route choice73 cited
  • 2007Predicting Bicycle Travel Speeds Along Different Facilities Using GPS Data: A Proof-of-Concept Model

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64 cited
  • 2015A quantum utility model for route choice in transport systems61 cited
  • 2017Empirical speed models for cycling in the Oslo road network57 cited
  • Cited by

    • 2025Cycling speed profiles from GPS data: Insights for conventional and electrified bicycles in Switzerland10 cited
    • 2019Improving GIS-based models for bicycling speed estimations8 cited
    • 2024Predicting Cyclist Speed in Urban Contexts: A Neural Network Approach4 cited
    • 2025Identification and investigation of cruising speeds from cycling GPS data3 cited