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Improving predictions of public transport usage during disturbances based on smart card data

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References

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2012Estimation of a disaggregate multimodal public transport Origin–Destination matrix from passive smartcard data from Santiago, Chile546 cited
2004The demand for public transport: a practical guide452 cited
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1999European Transport Conference223 cited
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2009Analyzing Multimodal Public Transport Journeys in London with Smart Card Fare Payment Data190 cited
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2010Travel Time and Transfer Analysis Using Transit Smart Card Data154 cited
2013Travelers’ preferences in multimodal networks: Design and results of a comprehensive series of choice experiments124 cited
2015Passenger Journey Destination Estimation From Automated Fare Collection System Data Using Spatial Validation93 cited
2015

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Identification and classification of public transport activity centres in Stockholm using passenger flows data

66 cited

2015Short-Term Prediction of Ridership on Public Transport with Smart Card Data65 cited

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2019Station-based average travel distance and its relationship with urban form and land use: An analysis of smart card data in Nanjing City, China39 cited
2019Calibration of a transit route choice model using revealed population data of smartcard in a multimodal transit network35 cited
2020Analysis of Transit Users’ Response Behavior in Case of Unplanned Service Disruptions32 cited
2021Characterization of COVID-19’s Impact on Mobility and Short-Term Prediction of Public Transport Demand in a Mid-Size City in Spain31 cited
2020An Integrated SWARA-WASPAS Group Decision Making Framework to Evaluate Smart Card Systems for Public Transportation28 cited
2018Workshop 8 report: Big data in the digital age and how it can benefit public transport users24 cited
2022Impact of Unplanned Long-Term Service Disruptions on Urban Public Transit Systems22 cited
2020A stated-preference intercept survey of transit-rider response to service disruptions17 cited
2020The effect of unexpected disruptions and information times on public transport passengers: a simulation study15 cited
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