Journal Articles
Journal Articles
[1]
B. Djordjevic et al.,
"An optimisation-based digital twin for automated operation of rail level crossings,"
Expert systems with applications, vol. 239, 2024.
[2]
Y. Song et al.,
"A state-based inverse reinforcement learning approach to model activity-travel choices behavior with reward function recovery,"
Transportation Research Part C : Emerging Technologies, vol. 158, 2024.
[3]
D. Leffler et al.,
"An adaptive route choice model for integrated fixed and flexible transit systems,"
Transportmetrica B : Transport Dynamics, vol. 12, no. 1, 2024.
[4]
C. Sánchez and I. Nordmark,
"Knowledge hub : ESEP4Freight's contribution to rail freight information,"
Global Railway Review, vol. 30, no. 1, pp. 38-39, 2024.
[5]
I. Johansson and A. Peterson,
"Rail platform allocation for reliable interchanges,"
Transportation Research Procedia, vol. 78, pp. 198-205, 2024.
[6]
Z. Zhang et al.,
"Improving 3-day deterministic air pollution forecasts using machine learning algorithms,"
Atmospheric Chemistry And Physics, vol. 24, no. 2, pp. 807-851, 2024.
[7]
O. Cats, S. Derrible and J. Chow,
"Special issue on "Reliability and resilience of emerging mobility systems", an editorial note,"
Transportmetrica B : Transport Dynamics, vol. 11, no. 1, pp. 1092-1094, 2023.
[8]
M. M. Zefreh et al.,
"Intention to use private autonomous vehicles in developed and developing countries : What are the differences among the influential factors, mediators, and moderators?,"
Travel Behaviour & Society, vol. 32, 2023.
[9]
L. Wang et al.,
"Human-centric multimodal deep (HMD) traffic signal control,"
IET Intelligent Transport Systems, vol. 17, no. 4, pp. 744-753, 2023.
[10]
B. Mo et al.,
"Ex Post Path Choice Estimation for Urban Rail Systems Using Smart Card Data : An Aggregated Time-Space Hypernetwork Approach,"
Transportation Science, vol. 57, no. 2, pp. 313-335, 2023.
[11]
K. Tuncel, H. N. Koutsopoulos and Z. Ma,
"An integrated ride-matching and vehicle-rebalancing model for shared mobility on-demand services,"
Computers & Operations Research, vol. 159, 2023.
[12]
H. Badia and E. Jenelius,
"Shared e-scooter micromobility : review of use patterns, perceptions and environmental impacts,"
Transport reviews, vol. 43, no. 5, pp. 811-837, 2023.
[13]
L. Kolkowski et al.,
"Measuring activity-based social segregation using public transport smart card data,"
Journal of Transport Geography, vol. 110, 2023.
[14]
M. M. Zefreh et al.,
"A data-driven decision support tool for public transport service analysis and provision,"
Transport Policy, vol. 135, pp. 82-90, 2023.
[15]
J. Y. Lin et al.,
"The equity of public transport crowding exposure,"
Journal of Transport Geography, vol. 110, 2023.
[16]
K. Y. Tiong, Z. Ma and C.-W. Palmqvist,
"Analyzing factors contributing to real-time train arrival delays using seemingly unrelated regression models,"
Transportation Research Part A : Policy and Practice, vol. 174, 2023.
[17]
B. Djordjevic, O. Fröidh and E. Krmac,
"Determinants of autonomous train operation adoption in rail freight : knowledge-based assessment with Delphi-ANP approach,"
Soft Computing - A Fusion of Foundations, Methodologies and Applications, vol. 27, no. 11, pp. 7051-7069, 2023.
[18]
J. Hatzenbühler et al.,
"Modular vehicle routing for combined passenger and freight transport,"
Transportation Research Part A : Policy and Practice, vol. 173, pp. 103688-103688, 2023.
[19]
M. Cebecauer et al.,
"Revealing representative day-types in transport networks using traffic data clustering,"
Journal of Intelligent Transportation Systems / Taylor & Francis, pp. 1-24, 2023.
[20]
[21]
B. Liu et al.,
"Passenger flow anomaly detection in urban rail transit networks with graph convolution network-informer and Gaussian Bayes models,"
Philosophical Transactions. Series A : Mathematical, physical, and engineering science, vol. 381, no. 2254, 2023.
[22]
Z. Liu et al.,
"Integrated optimization of timetable, bus formation, and vehicle scheduling in autonomous modular public transport systems,"
Transportation Research Part C : Emerging Technologies, vol. 155, 2023.
[23]
M. M. Zefreh, B. Edries and D. Esztergár-Kiss,
"Understanding the antecedents of hedonic motivation in autonomous vehicle technology acceptance domain : A cross-country analysis,"
Technology in society, vol. 74, 2023.
[24]
T. Liu, H. N. Koutsopoulos and Z. Ma,
"Modeling the Duration of the Impact of Unplanned Disruptions on Passenger Trips Using Smartcard Data in Urban Rail Systems,"
URBAN RAIL TRANSIT, vol. 9, no. 3, pp. 266-279, 2023.
[25]
Y. Sun et al.,
"Evaluation of Motorway Lane Control Strategies for Mixed Flow of Autonomous and Human-Driven Vehicles,"
Journal of Transportation Engineering, Part A: Systems, vol. 149, no. 11, pp. 1-12, 2023.
[26]
S. Peftitsi, E. Jenelius and O. Cats,
"Evaluating skip-stop policy in urban rail transit systems based on passenger cost,"
Journal of Public Transportation, vol. 25, 2023.
[27]
C.-W. Palmqvist, I. Johansson and H. Sipilä,
"A method to separate primary and secondary train delays in past and future timetables using macroscopic simulation,"
Transportation Research Interdisciplinary Perspectives, vol. 17, pp. 100747-100747, 2023.
[28]
Q. Zhang et al.,
"User-station attention inference using smart card data : a knowledge graph assisted matrix decomposition model,"
Applied intelligence (Boston), vol. 53, no. 19, pp. 21944-21960, 2023.
[29]
N. Minbashi et al.,
"Machine learning-assisted macro simulation for yard arrival prediction,"
Journal of Rail Transport Planning & Management, vol. 25, 2023.
[30]
K. Y. Tiong, Z. Ma and C.-W. Palmqvist,
"A review of data-driven approaches to predict train delays,"
Transportation Research Part C : Emerging Technologies, vol. 148, pp. 104027, 2023.
[31]
C. Zhong et al.,
"Online prediction of network-level public transport demand based on principle component analysis,"
Communications in Transportation Research, vol. 3, 2023.
[32]
Q. Zhang et al.,
"Mobility knowledge graph : review and its application in public transport,"
Transportation, 2023.
[33]
J. Högdahl and M. Bohlin,
"A Combined Simulation-Optimization Approach for Robust Timetabling on Main Railway Lines,"
Transportation Science, vol. 57, no. 1, pp. 52-81, 2023.
[34]
S. Cui et al.,
"Joint optimal vehicle and recharging scheduling for mixed bus fleets under limited chargers,"
Transportation Research Part E : Logistics and Transportation Review, vol. 180, 2023.
[35]
P. Zhang, H. N. Koutsopoulos and Z. Ma,
"DeepTrip : A Deep Learning Model for the Individual Next Trip Prediction With Arbitrary Prediction Times,"
IEEE transactions on intelligent transportation systems (Print), vol. 24, no. 6, pp. 5842-5855, 2023.
[36]
E. Jansson, N. O.E. Olsson and O. Fröidh,
"Challenges of replacing train drivers in driverless and unattended railway mainline systems—A Swedish case study on delay logs descriptions,"
Transportation Research Interdisciplinary Perspectives, vol. 21, pp. 100875-100875, 2023.
[37]
B. Djordjevic et al.,
"Efficient use of European rail freight corridors: current status and potential enablers,"
Transportation planning and technology (Print), vol. 47, no. 1, pp. 62-88, 2023.
[38]
B. Djordjevic, R. Maitra and B. Ghosh,
"Environmental efficiency assessment of Dublin Port using two-stage non-radial DEA model,"
Maritime Transport Research, vol. 4, pp. 100078-100078, 2023.
[39]
B. Berg Wincent, E. Jenelius and W. Burghout,
"Access distance to e-scooters : Analysis of app use and trip data in Stockholm,"
Journal of Cycling and Micromobility Research, pp. 100004-100004, 2023.
[40]
X. Chen, Z. Ma and Z. Li,
"Unplanned Disruption Analysis in Urban Railway Systems: Evidencefrom Hong Kong,"
Transportation Research Record, 2022.
[41]
A. Ait Ali, J. Eliasson and J. Warg,
"Are commuter train timetables consistent with passengers’ valuations of waiting times and in-vehicle crowding?,"
Transport Policy, vol. 116, pp. 188-198, 2022.
[42]
S. Peftitsi, E. Jenelius and O. Cats,
"Simulation-based evaluation of skip-stop policy in urban rail transit systems based on passenger cost,"
, 2022.
[43]
S. Peftitsi, E. Jenelius and O. Cats,
"Modelling the effect of real-time crowding information (RTCI) on passenger distribution in trains,"
, 2022.
[44]
E. Jenelius,
"Traveller Recurrence and Inter- versus Intratraveller Speed Variability : Analysis with Bluetooth Data,"
Journal of Advanced Transportation, vol. 2022, 2022.
[45]
Z. Ma and H. N. Koutsopoulos,
"Near-on-demand mobility. The benefits of user flexibility for ride-pooling services,"
Transportation Research Part C : Emerging Technologies, vol. 135, 2022.
[46]
H. Chen, J. Hatzenbühler and E. Jenelius,
"Pick-Up and Delivery Problem for Sequentially Consolidated Urban Transportation with Mixed and Multi-Pupropse Vehicle Fleet,"
Journal of Advanced Transportation, vol. 2022, 2022.
[47]
O. Cats and F. Ferranti,
"Unravelling individual mobility temporal patterns using longitudinal smart card data,"
Research in Transportation Business and Management (RTBM), vol. 43, pp. 100816, 2022.
[48]
E. Almlöf et al.,
"Will leisure trips be more affected than work trips by autonomous technology? : Modelling self-driving public transport and cars in Stockholm, Sweden,"
Transportation Research Part A : Policy and Practice, vol. 165, pp. 1-19, 2022.
[49]
S. M. H. Moosavi et al.,
"Understanding and Predicting the Usage of Shared Electric Scooter Services on University Campuses,"
Applied Sciences, vol. 12, no. 18, 2022.
[50]
J. Jin et al.,
"A GAN-Based Short-Term Link Traffic Prediction Approach for Urban Road Networks Under a Parallel Learning Framework,"
IEEE transactions on intelligent transportation systems (Print), vol. 23, no. 9, pp. 16185-16196, 2022.
Journal Articles (2017-12-31)
[1]
O. Cats and E. Jenelius,
"Beyond a complete failure: The impact of partial capacity degradation on public transport network vulnerability,"
Transportmetrica B : Transport Dynamics, vol. 6, no. 2, pp. 77-96, 2018.
[2]
I. Kristoffersson and L. Engelson,
"Estimating preferred departure times of road users in a large urban network,"
Transportation, vol. 45, no. 3, pp. 767-787, 2018.
[3]
J. Jin and X. Ma,
"A Decentralized Traffic Light Control System Based on Adaptive Learning,"
IFAC-PapersOnLine, vol. 50, no. 1, pp. 5301-5306, 2017.
[4]
J. Jin and X. Ma,
"A group-based traffic signal control with adaptive learning ability,"
Engineering applications of artificial intelligence, vol. 65, pp. 282-293, 2017.
[5]
M. Fadaei Oshyani, O. Cats and A. Bhaskar,
"A hybrid scheme for real-time prediction of bus trajectories : Hybrid Scheme for Real-Time Prediction,"
Journal of Advanced Transportation, vol. 50, no. 8, pp. 2130-2149, 2017.
[6]
J. Jin, X. Ma and I. Kosonen,
"A stochastic optimization framework for road traffic controls based on evolutionary algorithms and traffic simulation,"
Advances in Engineering Software, vol. 114, pp. 348-360, 2017.
[7]
M. Cebecauer and Ľ. Buzna,
"A versatile adaptive aggregation framework for spatially large discrete location-allocation problems,"
Computers & industrial engineering, vol. 111, pp. 364-380, 2017.
[8]
P. Suau-Sanchez, A. Voltes-Dorta and H. Rodríguez-Déniz,
"An assessment of the potential for self-connectivity at European airports in holiday markets,"
Tourism Management, vol. 62, pp. 54-64, 2017.
[9]
J. Jin, X. Ma and I. Kosonen,
"An intelligent control system for traffic lights with simulation-based evaluation,"
Control Engineering Practice, vol. 58, pp. 24-33, 2017.
[10]
M. I. Smaradottir et al.,
"Copeptin in patients with acute myocardial infarction and newly detected glucose abnormalities - A marker of increased stress susceptibility? : A report from the Glucose in Acute Myocardial Infarction cohort,"
Diabetes & Vascular Disease Research, vol. 14, no. 2, pp. 69-76, 2017.
[11]
G. Mwesige et al.,
"Effect of passing zone length on operation and safety of two-lane rural highways in Uganda,"
IATSS RESEARCH, vol. 41, no. 1, pp. 38-46, 2017.
[12]
I. Kristoffersson, L. Engelson and M. Börjesson,
"Efficiency vs equity : Conflicting objectives of congestion charges,"
Transport Policy, vol. 60, pp. 99-107, 2017.
[13]
V. Ritsinger et al.,
"Elevated levels of adipokines predict outcome after acute myocardial infarction : A long-term follow-up of the Glucose Tolerance in Patients with Acute Myocardial Infarction cohort,"
Diabetes & Vascular Disease Research, vol. 14, no. 2, pp. 77-87, 2017.
[14]
Y. O. Susilo and C. Liu,
"Examining the relationships between individual's time use and activity participations with their health indicators,"
European Transport Research Review, vol. 9, no. 2, 2017.
[15]
W. Zhang, E. Jenelius and X. Ma,
"Freight transport platoon coordination and departure time scheduling under travel time uncertainty,"
Transportation Research Part E : Logistics and Transportation Review, vol. 98, pp. 1-23, 2017.
[16]
J. Fu, E. Jenelius and H. N. Koutsopoulos,
"Identification of workstations in earthwork operations from vehicle GPS data,"
Automation in Construction, vol. 83, pp. 237-246, 2017.
[17]
Y. Zhang, E. Jenelius and K. Kottenhoff,
"Impact of real-time crowding information : A Stockholm metro case study,"
Public Transport, vol. 9, no. 3, pp. 483-499, 2017.
[18]
J. West and O. Cats,
"Individual and Synergetic Effects of Transit Service Improvement Strategies : Simulation and Validation,"
Journal of transportation engineering, vol. 143, no. 6, 2017.
[19]
G. Gentile and O. Cats,
"Introduction to the special issue on public transport modelling,"
EURO Journal on Transportation and Logistics, vol. 6, no. 3, pp. 219-220, 2017.
[20]
I. Johansson et al.,
"Look-ahead speed planning for heavy-duty vehicle platoons using traffic information,"
Transportation Research Procedia, vol. 22, pp. 561-569, 2017.
[21]
O. Cats and Z. Gkioulou,
"Modelling the Impacts of Public Transport Reliability and Travel Information on Passengers’ Waiting Time Uncertainty,"
EURO Journal on Transportation and Logistics, vol. 6, no. 3, 2017.
[22]
T. Ivert et al.,
"Platelet function one and three months after coronary bypass surgery in relation to once or twice daily dosing of acetylsalicylic acid,"
Thrombosis Research, vol. 149, pp. 64-69, 2017.
[23]
X. Ma, F. Al Khoury and J. Jin,
"Prediction of arterial travel time considering delay in vehicle re-identification,"
Transportation Research Procedia, vol. 22, pp. 625-634, 2017.
[24]
A. Bastian, M. Börjesson and J. Eliasson,
"Response to Wadud and Baierl : “Explaining ‘peak car’ with economic variables: An observation”,"
Transportation Research Part A : Policy and Practice, vol. 95, pp. 386-389, 2017.
[25]
N. Rathnayake et al.,
"Saliva and plasma levels of cardiac-related biomarkers in post-myocardial infarction patients.,"
Journal of Clinical Periodontology, vol. 44, no. 7, pp. 692-699, 2017.
[26]
M. Chen et al.,
"Service evaluation of public bicycle scheme from a user perspective,"
Transportation Research Record, vol. 2634, pp. 28-34, 2017.
[27]
B. Kjellström et al.,
"Symptoms of depression and their relation to myocardial infarction and periodontitis,"
European Journal of Cardiovascular Nursing, vol. 16, no. 6, pp. 468-474, 2017.
[28]
R. Fernandez Abenoza, O. Cats and Y. O. Susilo,
"Travel satisfaction with public transport : Determinants, user classes, regional disparities and their evolution,"
Transportation Research Part A : Policy and Practice, vol. 95, pp. 64-84, 2017.
[29]
M. Rahmani, H. N. Koutsopoulos and E. Jenelius,
"Travel time estimation from sparse floating car data with consistent path inference : A fixed point approach,"
Transportation Research Part C : Emerging Technologies, vol. 85, pp. 628-643, 2017.
[30]
M. Andersson, K. Brundell-Freij and J. Eliasson,
"Validation of aggregate reference forecasts for passenger transport,"
Transportation Research Part A : Policy and Practice, vol. 96, pp. 101-118, 2017.
[31]
A. Voltes-Dorta, H. Rodríguez-Déniz and P. Suau-Sánchez,
"Vulnerability of the European air transport network to major airport closures from the perspective of passenger delays : Ranking the most critical airports,"
Transportation Research Part A : Policy and Practice, vol. 96, pp. 119-145, 2017.
[32]
O. Cats, J. West and J. Eliasson,
"A dynamic stochastic model for evaluating congestion and crowding effects in transit systems,"
Transportation Research Part B : Methodological, vol. 89, pp. 43-57, 2016.
[33]
Q. Deng,
"A General Simulation Framework for Modeling and Analysis of Heavy-Duty Vehicle Platooning,"
IEEE transactions on intelligent transportation systems (Print), vol. 17, no. 11, pp. 3252-3262, 2016.
[34]
J. Jin and X. Ma,
"A Learning-based Adaptive Group-based Signal Control System under Oversaturated Conditions,"
IFAC-PapersOnLine, vol. 49, no. 5, pp. 291-296, 2016.
[35]
J. Jin and X. Ma,
"A Learning-based Adaptive Signal Control System with Function Approximation,"
IFAC-PapersOnLine, vol. 49, no. 3, pp. 5-10, 2016.
[36]
J. West, M. Börjesson and L. Engelson,
"Accuracy of the Gothenburg congestion charges,"
Transportation Research Part A : Policy and Practice, vol. 94, pp. 266-277, 2016.
[37]
J. Westin et al.,
"Achieving political acceptability for new transport infrastructure in congested urban regions,"
Transportation Research Part A : Policy and Practice, vol. 88, pp. 286-303, 2016.
[38]
A. Silvano, H. Koutsopoulos and X. Ma,
"Analysis of vehicle-bicycle interactions at unsignalized crossings : A probabilistic approach and application,"
Accident Analysis and Prevention, vol. 97, pp. 38-48, 2016.
[39]
C. Anderstig et al.,
"Congestion Charges and Labour Market Imperfections,"
Journal of Transport Economics and Policy, vol. 50, pp. 113-131, 2016.
[40]
D. B. E. Dharmowijoyo, Y. O. Susilo and A. Karlström,
"Day-to-day variability in travellers' activity-travel patterns in the Jakarta metropolitan area,"
Transportation, vol. 43, no. 4, pp. 601-621, 2016.
[41]
D. Asplund and J. Eliasson,
"Does uncertainty make cost-benefit analyses pointless?,"
Transportation Research Part A : Policy and Practice, vol. 92, pp. 195-205, 2016.
[42]
V. Ritsinger et al.,
"Elevated levels of adipokines predict outcome after acute myocardial infarction. Long-term follow-up of the GAMI cohort,"
EUROPEAN HEART JOURNAL, vol. 37, pp. 459-459, 2016.
[43]
O. Cats and G. Loutos,
"Evaluating the added-value of online bus arrival prediction schemes,"
Transportation Research Part A : Policy and Practice, vol. 86, pp. 35-55, 2016.
[44]
M. Fadaei and O. Cats,
"Evaluating the impacts and benefits of public transport design and operational measures,"
Transport Policy, 2016.
[45]
M. Beser Hugosson et al.,
"Evaluation of the Swedish car fleet model using recent applications,"
Transport Policy, vol. 49, pp. 30-40, 2016.
[46]
I. Johansson et al.,
"Glycosylated haemoglobin predicts mortality in patients with heart failure and unknown diabetes : insights from the Swedish heart failure registry (SwedeHF),"
EUROPEAN HEART JOURNAL, vol. 37, pp. 733-733, 2016.
[47]
I. Johansson et al.,
"Glycosylated haemoglobin predicts mortality in patients with heart failure and unknown diabetes : insights from the Swedish Heart Failure registry (SwedeHF),"
Diabetologia, vol. 59, pp. S532-S532, 2016.
[48]
J. Eliasson,
"Is congestion pricing fair? : Consumer and citizen perspectives on equity effects,"
Transport Policy, vol. 52, pp. 1-15, 2016.
[49]
O. Cats and M. Hartl,
"Modelling public transport on-board congestion : comparing schedule-based and agent-based assignment approaches and their implications,"
Journal of Advanced Transportation, vol. 50, no. 6, pp. 1209-1224, 2016.
[50]
N. Ahmad Termida, Y. O. Susilo and J. P. Franklin,
"Observing dynamic behavioural responses due to the extension of a tram line by using panel survey,"
Transportation Research Part A : Policy and Practice, vol. 86, pp. 78-95, 2016.