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Wang, Z. (author), Pel, A.J. (author), Verma, T. (author), Krishnakumari, P.K. (author), van Brakel, Peter (author), van Oort, N. (author)
Predictions on public transport ridership are beneficial as they allow for sufficient and cost-efficient deployment of vehicles. At an operational level, this relates to short-term predictions with lead times of less than an hour. Where conventional data sources on ridership, such as Automatic Fare Collection (AFC) data, may have longer lag...
conference paper 2022
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Wang, Z. (author), Pel, A.J. (author), Verma, T. (author), Krishnakumari, P.K. (author), van Brakel, Peter (author), van Oort, N. (author)
Predictions on Public Transport (PT) ridership are beneficial as they allow for sufficient and cost-efficient deployment of vehicles. On an operational level, this relates to short-term predictions with lead times of less than an hour. Where conventional data sources on ridership, such as Automatic Fare Collection (AFC) data, may have longer...
journal article 2022
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Wang, Ziyulong (author)
To address the increasing passenger demand in the coming years and make public transport less crowded and delayed, insights into predicted passenger flow are needed. A wide range of studies has used and validated that smart card data can be one of the sound bases for predicting short-term passenger demand. However, it also has several...
master thesis 2020