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Using Google’s Aggregated and Anonymized Trip Data to Support Freeway Corridor Management Planning in San Francisco, California
10 references·0 citing·43 second hop
Using Google’s Aggregated and Anonymized Trip Data to Support Freeway Corridor Management Planning in San Francisco, California (2017)Using Google’s Aggregated and Anonymized …High-Occupancy Toll Lane Decision Making: Income Effects on I-85 Express Lanes, Atlanta, Georgia (2015)High-Occupancy Toll Lane Deci…Analyzing Cell Phone Location Data for Urban Travel (2015)Analyzing Cell Phone Location…Validation of Origin–Destination Data from Bluetooth Reidentification and Aerial Observation (2014)Validation of Origin–Destinat…Travel Demand Management and the Big Scare (2014)Travel Demand Management and …Origin-Destination Estimation for Non-Commuting Trips Using Location-Based Social Networking Data (2014)Origin-Destination Estimation…Location-Based Social Networking Data (2014)Location-Based Social Network…Development of origin–destination matrices using mobile phone call data (2014)Development of origin–destina…Estimating Dynamic Origin-Destination Data and Travel Demand Using Cell Phone Network Data (2013)Estimating Dynamic Origin-Des…Generating Route-Specific Origin–Destination Tables Using Bluetooth Technology (2012)Generating Route-Specific Ori…Generating Origin–Destination Matrices from Mobile Phone Trajectories (2010)Generating Origin–Destination…Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Limits of Predictability in Human Mobility (2010)Modelling the scaling properties of human mobility (2010)Understanding individual routing behaviour (2016)Exploring the potential of mobile phone records and online route planners for dynamic accessibility analysis (2018)Inferring dynamic origin-destination flows by transport mode using mobile phone data (2019)Find me if you can (2010)You are where you tweet (2010)Friendship and mobility (2011)An adaptive hawkes process formulation for estimating time-of-day zonal trip arrivals with location-based social networking check-in data (2017)Inferring Activities from Social Media Data (2017)Feasibility of estimating travel demand using geolocations of social media data (2021)The Estimation of an Origin-Destination Matrix from Traffic Counts (1983)Transportation Systems Engineering: Theory and Methods (2001)Analysis of Household Survey Sample Size in Trip Modelling Process (2016)A DBSCAN-based framework to mine travel patterns from origin-destination matrices: Proof-of-concept on proxy static OD from Brisbane (2021)Sidewalk networks: Review and outlook (2023)Nonresponse Rates and Nonresponse Bias in Household Surveys (2006)Understanding individual human mobility patterns (2008)A universal model for mobility and migration patterns (2012)Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Extracting origin destination information from mobile phone data (2002)Deriving origin–destination data from a mobile phone network (2007)Investigating the Mobile Phone Data to Estimate the Origin Destination Flow and Analysis; Case Study: Paris Region (2015)Combining Bayesian Inference and Clustering for Transport Mode Detection from Sparse and Noisy Geolocation Data (2019)An Interdisciplinary Survey on Origin-destination Flows Modeling: Theory and Techniques (2024)Assessing Travel Demand Management for the Summer Olympic Games (2011)The role of businesses in facilitating voluntary travel behaviour change - Insights from the London 2012 Olympic Games (2019)Understanding changes in traffic demand during the Tokyo 2020 Olympic and Paralympic Games (2024)Qatar’s success story during FIFA world Cup 2022: Role of travel demand management and impact on travel behavior (2025)A statistical theory of spatial distribution models (1967)From cellular positioning data to trajectories: Steps towards a more accurate mobility exploration (2020)Human settlement value assessment from a place perspective: Considering human dynamics and perceptions in house price modeling (2021)Travel Time and Origin-Destination Data Collection using Bluetooth MAC Address Readers (2010)Integrating mesoscopic dynamic traffic assignment with agent-based travel behavior models for cumulative land development impact analysis (2018)A Framework for the Comparative Analysis of Multi-Modal Travel Demand: Case Study on Brisbane Network (2021)The value of time and reliability: measurement from a value pricing experiment (2001)Uncovering the Distribution of Motorists' Preferences for Travel Time and Reliability (2005)Valuing time and reliability: assessing the evidence from road pricing demonstrations (2005)A Primal-Dual Algorithm for Link Dependent Origin Destination Matrix Estimation (2016)Origin-Destination Matrix Estimation Using Big Traffic Data: A Structural Perspective (2019)
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References

  • 2014Development of origin–destination matrices using mobile phone call data508 cited
  • 2015Analyzing Cell Phone Location Data for Urban Travel180 cited
  • 2014Origin-Destination Estimation for Non-Commuting Trips Using Location-Based Social Networking Data62 cited
  • 2010Generating Origin–Destination Matrices from Mobile Phone Trajectories57 cited
  • 2013Estimating Dynamic Origin-Destination Data and Travel Demand Using Cell Phone Network Data55 cited
  • 2012Generating Route-Specific Origin–Destination Tables Using Bluetooth Technology44 cited
  • 2014Location-Based Social Networking Data38 cited
  • 2014Validation of Origin–Destination Data from Bluetooth Reidentification and Aerial Observation24 cited
  • 2014Travel Demand Management and the Big Scare14 cited
  • 2015High-Occupancy Toll Lane Decision Making: Income Effects on I-85 Express Lanes, Atlanta, Georgia7 cited

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