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2025 Journal Article Congestion pricing in multi-modal networks: an application of deep reinforcement learningParishad, Nasser, Yildirimoglu, Mehmet and Hickman, Mark (2025). Congestion pricing in multi-modal networks: an application of deep reinforcement learning. Transportation Research Part C: Emerging Technologies, 177 105166, 105166. doi: 10.1016/j.trc.2025.105166 |
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2025 Journal Article Investigating customers’ typical longitudinal behavioural responses in a large-scale mobility-as-a-service trialChen, Xin, Lu, Ying, Whitehead, Jake and Hickman, Mark (2025). Investigating customers’ typical longitudinal behavioural responses in a large-scale mobility-as-a-service trial. Transportation. doi: 10.1007/s11116-025-10643-4 |
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2025 Journal Article Comparing the spatial temporal dynamics of public transport ridership before and after the launch of MaaS trial: a case study of university of Queensland, Brisbane, AustraliaLu, Ying, Chen, Xin and Hickman, Mark (2025). Comparing the spatial temporal dynamics of public transport ridership before and after the launch of MaaS trial: a case study of university of Queensland, Brisbane, Australia. Transportation, 1-27. doi: 10.1007/s11116-025-10636-3 |
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2025 Journal Article Behavior Analysis of Shared Micro-Mobility Service in Mobility as a Service: Empirical Evidence from a Large-Scale Trial in a University CommunityChen, Xin, Hickman, Mark and Lu, Ying (2025). Behavior Analysis of Shared Micro-Mobility Service in Mobility as a Service: Empirical Evidence from a Large-Scale Trial in a University Community. Transportation Research Record: Journal of the Transportation Research Board, 1-13. doi: 10.1177/03611981251327580 |
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2025 Journal Article Zone substations' readiness to embrace electric vehicle adoption: Brisbane case studyFuentes, Abel Quintero, Hickman, Mark and Whitehead, Jake (2025). Zone substations' readiness to embrace electric vehicle adoption: Brisbane case study. Energy, 322 135519, 135519-322. doi: 10.1016/j.energy.2025.135519 |
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2023 Journal Article MSGNN: A Multi-structured Graph Neural Network model for real-time incident prediction in large traffic networksTran, Thanh, He, Dan, Kim, Jiwon and Hickman, Mark (2023). MSGNN: A Multi-structured Graph Neural Network model for real-time incident prediction in large traffic networks. Transportation Research Part C: Emerging Technologies, 156 104354. doi: 10.1016/j.trc.2023.104354 |
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2023 Journal Article Estimation of macroscopic fundamental diagram solely from probe vehicle trajectories with an unknown penetration rateSaffari, Elham, Yildirimoglu, Mehmet and Hickman, Mark (2023). Estimation of macroscopic fundamental diagram solely from probe vehicle trajectories with an unknown penetration rate. IEEE Transactions on Intelligent Transportation Systems, 24 (12), 14970-14981. doi: 10.1109/tits.2023.3303439 |
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2022 Journal Article Data fusion for estimating Macroscopic Fundamental Diagram in large-scale urban networksSaffari, Elham, Yildirimoglu, Mehmet and Hickman, Mark (2022). Data fusion for estimating Macroscopic Fundamental Diagram in large-scale urban networks. Transportation Research Part C: Emerging Technologies, 137 103555, 103555. doi: 10.1016/j.trc.2022.103555 |
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2021 Journal Article Relationship between programmed heavy vehicle inspections and traffic safetyAssemi, Behrang, Hickman, Mark and Paz, Alexander (2021). Relationship between programmed heavy vehicle inspections and traffic safety. Transportation Research Record, 2675 (10) 03611981211016458, 1420-1430. doi: 10.1177/03611981211016458 |
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2021 Journal Article Advanced systems in public transport, with a touch of dataTrépanier, Martin and Hickman, Mark (2021). Advanced systems in public transport, with a touch of data. Public Transport, 13 (3), 455-456. doi: 10.1007/s12469-021-00288-8 |
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2020 Journal Article A methodology for identifying critical links and estimating macroscopic fundamental diagram in large-scale urban networksSaffari, Elham, Yildirimoglu, Mehmet and Hickman, Mark (2020). A methodology for identifying critical links and estimating macroscopic fundamental diagram in large-scale urban networks. Transportation Research Part C: Emerging Technologies, 119 102743, 102743. doi: 10.1016/j.trc.2020.102743 |
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2020 Journal Article Modeling Mode Choice of Air Passengers’ Ground Access to Brisbane AirportPasha, Md Mosabbir, Hickman, Mark D. and Prato, Carlo G. (2020). Modeling Mode Choice of Air Passengers’ Ground Access to Brisbane Airport. Transportation Research Record, 2674 (11), 756-767. doi: 10.1177/0361198120949534 |
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2020 Journal Article Network design with elastic demand and dynamic passenger assignment to assess the performance of transit servicesRanjbari, Andisheh, Hickman, Mark and Chiu, Yi-Chang (2020). Network design with elastic demand and dynamic passenger assignment to assess the performance of transit services. Journal of Transportation Engineering, Part A: Systems, 146 (5) 04020030, 04020030. doi: 10.1061/jtepbs.0000326 |
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2020 Journal Article Improving alighting stop inference accuracy in the trip chaining method using neural networksAssemi, Behrang, Alsger, Azalden, Moghaddam, Mahboobeh, Hickman, Mark and Mesbah, Mahmoud (2020). Improving alighting stop inference accuracy in the trip chaining method using neural networks. Public Transport, 12 (1), 89-121. doi: 10.1007/s12469-019-00218-9 |
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2020 Journal Article A network design problem formulation and solution procedure for intercity transit servicesRanjbari, Andisheh, Hickman, Mark and Chiu, Yi-Chang (2020). A network design problem formulation and solution procedure for intercity transit services. Transportmetrica A: Transport Science, 16 (3), 1156-1175. doi: 10.1080/23249935.2020.1719547 |
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2020 Journal Article Transport-related walking among young adults: when and why?Assemi, Behrang, Zahnow, Renee, Zapata-Diomedi, Belen, Hickman, Mark and Corcoran, Jonathan (2020). Transport-related walking among young adults: when and why?. BMC Public Health, 20 (1) 244, 244. doi: 10.1186/s12889-020-8338-0 |
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2019 Journal Article An intelligent decision support system prototype for hinterland port logisticsIrannezhad, Elnaz, Prato, Carlo G. and Hickman, Mark (2019). An intelligent decision support system prototype for hinterland port logistics. Decision Support Systems, 130 113227, 113227. doi: 10.1016/j.dss.2019.113227 |
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2019 Journal Article Temporal validation of a multimodal transit assignment modelRahbar, Mohadeseh, Hickman, Mark, Mesbah, Mahmoud and Tavassoli, Ahmad (2019). Temporal validation of a multimodal transit assignment model. Case Studies on Transport Policy, 8 (2), 535-541. doi: 10.1016/j.cstp.2019.11.006 |
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2019 Journal Article Special issue on dynamic traffic assignment for general transport networksBliemer, Michiel C. J., Waller, S. Travis, Bell, Michael G. H. and Hickman, Mark D. (2019). Special issue on dynamic traffic assignment for general transport networks. Transportation Research Part B: Methodological, 126, 307-308. doi: 10.1016/j.trb.2019.06.002 |
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2019 Journal Article Calibrating a transit assignment model using smart card data in a large-scale multi-modal transit networkTavassoli, Ahmad, Mesbah, Mahmoud and Hickman, Mark (2019). Calibrating a transit assignment model using smart card data in a large-scale multi-modal transit network. Transportation, 47 (5), 2133-2156. doi: 10.1007/s11116-019-10004-y |
