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Rafał Kucharski
Rafał Kucharski
Jagiellonian University - Group of Machine Learning Methods
Verifierad e-postadress på uj.edu.pl - Startsida
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Modelling the effects of real-time crowding information in urban public transport systems
A Drabicki, R Kucharski, O Cats, A Szarata
Transportmetrica A: Transport Science 17 (4), 675-713, 2021
81*2021
Estimating macroscopic volume delay functions with the traffic density derived from measured speeds and flows
R Kucharski, A Drabicki
Journal of Advanced Transportation 2017 (1), 4629792, 2017
752017
Beyond the dichotomy: How ride-hailing competes with and complements public transport
O Cats, R Kucharski, SR Danda, M Yap
Plos one 17 (1), e0262496, 2022
722022
Exact matching of attractive shared rides (ExMAS) for system-wide strategic evaluations
R Kucharski, O Cats
Transportation Research Part B: Methodological 139, 285-310, 2020
692020
Impact of commuting, time budgets, and activity durations on modal disparity in accessibility to supermarkets
MA Niedzielski, R Kucharski
Transportation Research Part D: Transport and Environment 75, 106-120, 2019
482019
Simulation of rerouting phenomena in Dynamic Traffic Assignment with the Information Comply Model
R Kucharski, G Gentile
Transportation Research Part B: Methodological 126, 414-441, 2019
47*2019
Simulating two-sided mobility platforms with MaaSSim
R Kucharski, O Cats
Plos one 17 (6), e0269682, 2022
322022
Mitigating bus bunching with real-time crowding information
A Drabicki, R Kucharski, O Cats
Transportation 50 (3), 1003-1030, 2023
31*2023
Should I stay or should I board? Willingness to wait with real-time crowding information in urban public transport
A Drabicki, O Cats, R Kucharski, A Fonzone, A Szarata
Research in Transportation Business & Management 47, 100963, 2023
31*2023
Low-dimensional model for bike-sharing demand forecasting that explicitly accounts for weather data
G Cantelmo, R Kucharski, C Antoniou
Transportation research record 2674 (8), 132-144, 2020
302020
If you are late, everyone is late: late passenger arrival and ride-pooling systems' performance
R Kucharski, A Fielbaum, J Alonso-Mora, O Cats
Transportmetrica A: Transport Science 17 (4), 1077-1100, 2021
272021
How to split the costs and charge the travellers sharing a ride? aligning system’s optimum with users’ equilibrium
A Fielbaum, R Kucharski, O Cats, J Alonso-Mora
European Journal of Operational Research 301 (3), 956-973, 2022
262022
Evolution of labour supply in ridesourcing
A de Ruijter, O Cats, R Kucharski, H van Lint
Transportmetrica B: Transport Dynamics 10 (1), 599-626, 2022
242022
Modelling virus spreading in ride-pooling networks
R Kucharski, O Cats, J Sienkiewicz
Scientific Reports 11 (1), 1-11, 2021
24*2021
The shareability potential of ride-pooling under alternative spatial demand patterns
J Soza-Parra, R Kucharski, O Cats
Transportmetrica A: Transport Science 20 (2), 2140022, 2024
16*2024
Using city-bike stopovers to reveal spatial patterns of urban attractiveness
K Banet, V Naumov, R Kucharski
Current Issues in Tourism 25 (18), 2887-2904, 2022
142022
Multichannel queueing behaviour in urban bicycle traffic
R Kucharski, A Drabicki, K Żyłka, A Szarata
European Journal of Transport and Infrastructure Research 19 (2), 2019
11*2019
MODELLING THE PUBLIC TRANSPORT CAPACITY CONSTRAINTS’IMPACT ON PASSENGER PATH CHOICES IN TRANSIT ASSIGNMENT MODELS
A Drabicki, R Kucharski, A Szarata
Archives of Transport, 2017
112017
A low dimensional model for bike sharing demand forecasting
C Guido, K Rafał, A Constantinos
2019 6th International Conference on Models and Technologies for Intelligent …, 2019
102019
Modeling information spread processes in dynamic traffic networks
R Kucharski, G Gentile
Challenge of Transport Telematics: 16th International Conference on …, 2016
102016
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Artiklar 1–20