Data to the people: a review of public and proprietary data for transport models
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Rolf Moeckel | Constantinos Antoniou | Guido Cantelmo | Nico Kuehnel | Vishal Mahajan | Aikaterini Intzevidou | R. Moeckel | C. Antoniou | Guido Cantelmo | Nico Kuehnel | Vishal Mahajan | Aikaterini Intzevidou
[1] Frederika Welle Donker,et al. Open Data and Beyond , 2016, ISPRS Int. J. Geo Inf..
[2] G. Bowker,et al. An International Framework to Promote Access to Data , 2004, Science.
[3] Tsvi Kuflik,et al. Enhancing transport data collection through social media sources: methods, challenges and opportunities for textual data , 2015 .
[4] Jędrzej Gadziński,et al. Perspectives of the use of smartphones in travel behaviour studies: Findings from a literature review and a pilot study , 2018 .
[5] Yannis Charalabidis,et al. Benefits, Adoption Barriers and Myths of Open Data and Open Government , 2012, Inf. Syst. Manag..
[6] David Fisher,et al. Geolocated social media as a rapid indicator of park visitation and equitable park access , 2018, Comput. Environ. Urban Syst..
[7] Peter White,et al. The Potential of Public Transport Smart Card Data , 2005 .
[8] Stephane Hess,et al. Modelling departure time choice using mobile phone data , 2019 .
[9] Darcy M. Bullock,et al. Estimating Route Choice and Travel Time Reliability with Field Observations of Bluetooth Probe Vehicles , 2011 .
[10] Fang Liu,et al. Inferring driving trajectories based on probabilistic model from large scale taxi GPS data , 2018, Physica A: Statistical Mechanics and its Applications.
[11] Lidia P. Kostyniuk,et al. Using GPS Data to Understand Driving Behavior , 2008 .
[12] Jean Wolf,et al. TRIP RATE ANALYSIS IN GPS-ENHANCED PERSONAL TRAVEL SURVEYS. IN: TRANSPORT SURVEY QUALITY AND INNOVATION , 2003 .
[13] Kirsten Elger,et al. Utilizing the International Geo Sample Number Concept in Continental Scientific Drilling During ICDP Expedition COSC-1 , 2017, Data Sci. J..
[14] P. Stopher,et al. Assessing the accuracy of the Sydney Household Travel Survey with GPS , 2007 .
[15] E. Murakami,et al. Can using global positioning system (GPS) improve trip reporting , 1999 .
[16] Alexander Zipf,et al. Fine-resolution population mapping using OpenStreetMap points-of-interest , 2014, Int. J. Geogr. Inf. Sci..
[17] Yusak O. Susilo,et al. Transportation mode detection – an in-depth review of applicability and reliability , 2017 .
[18] J. David Porter,et al. A cluster analysis approach for differentiating transportation modes using Bluetooth sensor data , 2018, J. Intell. Transp. Syst..
[19] Adam Rahbee,et al. Origin and Destination Estimation in New York City with Automated Fare System Data , 2002 .
[20] Rajesh Krishnan,et al. Reliability of Bluetooth Technology for Travel Time Estimation , 2015, J. Intell. Transp. Syst..
[21] Peter R. Stopher,et al. Quantifying the Difference Between Self-Reported and Global Positioning Systems-Measured Journey Durations: A Systematic Review , 2013 .
[22] Kai Nagel,et al. The MATSim Open Berlin Scenario: A multimodal agent-based transport simulation scenario based on synthetic demand modeling and open data , 2019, ANT/EDI40.
[23] Johan Wideberg,et al. Deriving origin destination data from a mobile phone network , 2007 .
[24] Ahmad Tavassoli,et al. Application of smart card data in validating a large-scale multi-modal transit assignment model , 2017, Public Transport.
[25] Monica Palmirani,et al. Open Government Data Licensing Framework , 2015, EGOVIS.
[26] Ashish Bhaskar,et al. Fundamental understanding on the use of Bluetooth scanner as a complementary transport data , 2013 .
[27] Alexander Zipf,et al. Toward mapping land-use patterns from volunteered geographic information , 2013, Int. J. Geogr. Inf. Sci..
[28] Eazaz Sadeghvaziri,et al. Comprehensive Review of Travel Behavior and Mobility Pattern Studies That Used Mobile Phone Data , 2016 .
[29] Dominik Papinski,et al. Exploring the route choice decision-making process: A comparison of planned and observed routes obtained using person-based GPS , 2009 .
[30] Jiří Slavík,et al. Estimation of a route choice model for urban public transport using smart card data , 2014 .
[31] Eirin Olaussen Ryeng,et al. Evaluating Bluetooth and Wi-Fi Sensors as a Tool for Collecting Bicycle Speed at Varying Gradients☆ , 2016 .
[32] Hjp Harry Timmermans,et al. Transportation mode recognition using GPS and accelerometer data , 2013 .
[33] Tijs Neutens,et al. Identifying public transport gaps using time-dependent accessibility levels , 2015 .
[34] Yang Yang,et al. Optimization Model of Taxi Fleet Size Based on GPS Tracking Data , 2019, Sustainability.
[35] Hansi Senaratne,et al. A review of volunteered geographic information quality assessment methods , 2017, Int. J. Geogr. Inf. Sci..
[36] Reza Tolouei,et al. Origin-Destination Trip Matrix Development: Conventional Methods versus Mobile Phone Data , 2017 .
[37] David Watling,et al. Identifying road user classes based on repeated trip behaviour using Bluetooth data , 2018, Transportation Research Part A: Policy and Practice.
[38] David Veneziano,et al. Pilot Test of Automatic Vehicle Location on Snow Plows: Technical Memorandum 2: Pre-Pilot Test Results , 2007 .
[39] Jari Saramäki,et al. A collection of public transport network data sets for 25 cities , 2018, Scientific Data.
[40] B. V. Loenen,et al. Sustainable Business Models for Public Sector Open Data Providers , 2016 .
[41] Peter Suber,et al. Gratis and libre open access , 2008 .
[42] Rolf Moeckel,et al. Noise Shielding in an Agent-Based Transport Model Using Volunteered Geographic Data , 2019, ANT/EDI40.
[43] Emmanouil Chaniotakis,et al. Built Environment Factors Affecting Bike Sharing Ridership: Data-Driven Approach for Multiple Cities , 2019, Transportation Research Record: Journal of the Transportation Research Board.
[44] Phonon anharmonicities and ultrafast dynamics in epitaxial Sb2Te3 , 2020, Scientific Reports.
[45] Frederika Welle Donker,et al. How to assess the success of the open data ecosystem? , 2017, Int. J. Digit. Earth.
[46] Robert Weibel,et al. Transport mode detection based on mobile phone network data: A systematic review , 2019, Transportation Research Part C: Emerging Technologies.
[47] David M Levinson,et al. Developing a Comprehensive U.S. Transit Accessibility Database , 2015 .
[48] Nicolas Saunier,et al. Analysis of Pedestrian Travel with Static Bluetooth Sensors , 2012 .
[49] E. Collantes. Santiago de Chile , 2004 .
[50] Ashish Bhaskar,et al. Bluetooth Vehicle Trajectory by Fusing Bluetooth and Loops: Motorway Travel Time Statistics , 2014, IEEE Transactions on Intelligent Transportation Systems.
[51] Constantinos Antoniou,et al. Mapping Social Media for Transportation Studies , 2016, IEEE Intelligent Systems.
[52] Timothy F Welch,et al. Big data in public transportation: a review of sources and methods , 2019, Transport Reviews.
[53] Qing He,et al. Forecasting the Subway Passenger Flow Under Event Occurrences With Social Media , 2017, IEEE Transactions on Intelligent Transportation Systems.
[54] Greg Lindsey,et al. Photos, tweets, and trails: Are social media proxies for urban trail use? , 2017 .
[55] Lasse Bienzeisler,et al. Development of an Agent-Based Transport Model for the City of Hanover Using Empirical Mobility Data and Data Fusion , 2020, Transportation Research Procedia.
[56] Mahmoud Mesbah,et al. Applications of transit smart cards beyond a fare collection tool: a literature review , 2018 .
[57] Katleen Janssen,et al. The influence of the PSI directive on open government data: An overview of recent developments , 2011, Gov. Inf. Q..
[58] Martin Trépanier,et al. Individual Trip Destination Estimation in a Transit Smart Card Automated Fare Collection System , 2007, J. Intell. Transp. Syst..
[59] Charisma F. Choudhury,et al. Emerging Big Data Sources for Public Transport Planning: A Systematic Review on Current State of Art and Future Research Directions , 2019, Journal of the Indian Institute of Science.
[60] Yunyan Du,et al. Accessibility to urban parks for elderly residents: Perspectives from mobile phone data , 2019, Landscape and Urban Planning.
[61] Scott Smith,et al. General Modeling Network Specification: documentation, software, and data , 2020 .
[62] Yu Cui,et al. Forecasting current and next trip purpose with social media data and Google Places , 2018, Transportation Research Part C: Emerging Technologies.
[63] Carlo Ratti,et al. Transportation mode inference from anonymized and aggregated mobile phone call detail records , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.
[64] H. Mahmassani,et al. Incorporating social media in travel and activity choice models: conceptual framework and exploratory analysis , 2018 .
[65] Yannis Charalabidis,et al. A taxonomy of open government data research areas and topics , 2016, J. Organ. Comput. Electron. Commer..
[66] Anastasia A. Lantseva,et al. Modeling Transport Accessibility with Open Data: Case Study of St. Petersburg , 2016 .
[67] Jennifer Dill,et al. Where do cyclists ride? A route choice model developed with revealed preference GPS data , 2012 .
[68] Juan Carlos García-Palomares,et al. Social media and urban mobility: Using twitter to calculate home-work travel matrices , 2019, Cities.
[69] Emmanouil N. Barmpounakis,et al. On the new era of urban traffic monitoring with massive drone data: The pNEUMA large-scale field experiment , 2020 .
[70] Zhaohui Wu,et al. This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1 Land-Use Classification Using Taxi GPS Traces , 2022 .
[71] O. Järv,et al. Understanding monthly variability in human activity spaces: A twelve-month study using mobile phone call detail records , 2014 .
[72] Frederika Welle Donker,et al. How to assess the success of the open data ecosystem? , 2017 .
[73] Carlos Carmona,et al. Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring , 2010 .
[74] Patrick Bonnel,et al. Origin-Destination estimation using mobile network probe data , 2018 .
[75] T. Rashidi,et al. Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges , 2017 .
[76] Mark Bradley,et al. Activity-Based Travel Demand Models: A Primer , 2014 .
[77] Ling Bian,et al. From traces to trajectories: How well can we guess activity locations from mobile phone traces? , 2014 .
[78] Constantinos Antoniou,et al. Use of Geotagged Social Media in Urban Settings: Empirical Evidence on Its Potential from Twitter , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.
[79] Catherine Morency,et al. Smart card data use in public transit: A literature review , 2011 .
[80] Karin Pfeffer,et al. Survey-based socio-economic data from slums in Bangalore, India , 2018, Scientific data.
[81] Randy Holden,et al. Data-driven innovation : big data for growth and well-being , 2015 .
[82] Rolf Moeckel,et al. The usage of location based big data and trip planning services for the estimation of a long-distance travel demand model. Predicting the impacts of a new high speed rail corridor , 2018 .
[83] Shanjiang Zhu,et al. Potentials of using social media to infer the longitudinal travel behavior: A sequential model-based clustering method , 2017 .
[84] Haris N. Koutsopoulos,et al. A Synthesis of emerging data collection technologies and their impact on traffic management applications , 2011 .
[85] Johannes Schlaich,et al. Analyzing Route Choice Behavior with Mobile Phone Trajectories , 2010 .
[86] M. Mildner,et al. Re-epithelialization and immune cell behaviour in an ex vivo human skin model , 2020, Scientific Reports.
[87] Yi Yang,et al. An Extended Semi-Supervised Regression Approach with Co-Training and Geographical Weighted Regression: A Case Study of Housing Prices in Beijing , 2016, ISPRS Int. J. Geo Inf..
[88] Julie McLeod,et al. Opening research data: issues and opportunities , 2014 .
[89] Constantinos Antoniou,et al. Inferring Activities from Social Media Data , 2017 .
[90] D. Watling,et al. Big data and understanding change in the context of planning transport systems , 2019, Journal of Transport Geography.