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2024 Journal Article Building a less intimidating cycling environment for women: a structural equation modeling analysis based on a VR-based laboratory experimentKhademi, Navid, Naeinizadeh, Mohammadamin, Firoozi Yeganeh, Sayna, Behmanesh, Arian, Ekramifard, Ali, Chaiyasarn, Krisada, Zheng, Zuduo, Arbabpour Bidgoli, Mohammad, Azarmi, Hossein, Tarvirdizadeh, Bahram and Hadi, Alireza (2024). Building a less intimidating cycling environment for women: a structural equation modeling analysis based on a VR-based laboratory experiment. Transportation Research Part F: Traffic Psychology and Behaviour, 100, 431-457. doi: 10.1016/j.trf.2023.12.001 |
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2024 Journal Article ABAFT: an adaptive weight-based fusion technique for travel time estimation using multi-source data with different confidence and spatial coverageRespati, Sara, Chung, Edward, Zheng, Zuduo and Bhaskar, Ashish (2024). ABAFT: an adaptive weight-based fusion technique for travel time estimation using multi-source data with different confidence and spatial coverage. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 28 (6), 867-880. doi: 10.1080/15472450.2023.2228198 |
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2023 Journal Article Continuum modeling of freeway traffic flows: state-of-the-art, challenges and future directions in the era of connected and automated vehiclesMohammadian, Saeed, Zheng, Zuduo, Haque, Md. Mazharul and Bhaskar, Ashish (2023). Continuum modeling of freeway traffic flows: state-of-the-art, challenges and future directions in the era of connected and automated vehicles. Communications in Transportation Research, 3 100107, 1-25. doi: 10.1016/j.commtr.2023.100107 |
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2023 Journal Article Stability and extension of a car-following model for human-driven connected vehiclesSun, Jie, Zheng, Zuduo, Sharma, Anshuman and Sun, Jian (2023). Stability and extension of a car-following model for human-driven connected vehicles. Transportation Research Part C: Emerging Technologies, 155 104317, 1-17. doi: 10.1016/j.trc.2023.104317 |
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2023 Journal Article A hybrid modelling framework for the estimation of dynamic origin–destination flowsKumarage, Sakitha, Yildirimoglu, Mehmet and Zheng, Zuduo (2023). A hybrid modelling framework for the estimation of dynamic origin–destination flows. Transportation Research Part B: Methodological, 176 102804, 1-27. doi: 10.1016/j.trb.2023.102804 |
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2023 Journal Article Car-following crash risk analysis in a connected environment: a Bayesian non-stationary generalised extreme value modelNazir, Faizan, Ali, Yasir, Sharma, Anshuman, Zheng, Zuduo and Haque, Md Mazharul (2023). Car-following crash risk analysis in a connected environment: a Bayesian non-stationary generalised extreme value model. Analytic Methods in Accident Research, 39 100278, 1-19. doi: 10.1016/j.amar.2023.100278 |
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2023 Journal Article Demand and state estimation for perimeter control in large-scale urban networksKumarage, Sakitha, Yildirimoglu, Mehmet and Zheng, Zuduo (2023). Demand and state estimation for perimeter control in large-scale urban networks. Transportation Research Part C: Emerging Technologies, 153 104184, 104184. doi: 10.1016/j.trc.2023.104184 |
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2023 Journal Article NET-RAT: Non-equilibrium traffic model based on risk allostasis theoryMohammadian, Saeed, Zheng, Zuduo, Haque, Mazharul and Bhaskar, Ashish (2023). NET-RAT: Non-equilibrium traffic model based on risk allostasis theory. Transportation Research Part A: Policy and Practice, 174 103731. doi: 10.1016/j.tra.2023.103731 |
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2023 Journal Article Calibrating lane-changing models: two data-related issues and a general method to extract appropriate dataAli, Yasir, Zheng, Zuduo and Bliemer, Michiel C.J. (2023). Calibrating lane-changing models: two data-related issues and a general method to extract appropriate data. Transportation Research Part C: Emerging Technologies, 152 104182, 104182. doi: 10.1016/j.trc.2023.104182 |
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2023 Journal Article A Bayesian hierarchical approach to the joint modelling of Revealed and stated choicesLi, Zili, Washington, Simon P., Zheng, Zuduo and Prato, Carlo G. (2023). A Bayesian hierarchical approach to the joint modelling of Revealed and stated choices. Journal of Choice Modelling, 47 100419, 100419. doi: 10.1016/j.jocm.2023.100419 |
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2023 Journal Article Autonomous vehicle’s impact on traffic: empirical evidence from Waymo Open Dataset and implications from modellingHu, Xiangwang, Zheng, Zuduo, Chen, Danjue and Sun, Jian (2023). Autonomous vehicle’s impact on traffic: empirical evidence from Waymo Open Dataset and implications from modelling. IEEE Transactions on Intelligent Transportation Systems, 24 (6), 1-14. doi: 10.1109/tits.2023.3258145 |
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2023 Journal Article Assessing a connected environment's safety impact during mandatory lane-changing: a block maxima approachAli, Yasir, Haque, Md. Mazharul and Zheng, Zuduo (2023). Assessing a connected environment's safety impact during mandatory lane-changing: a block maxima approach. IEEE Transactions on Intelligent Transportation Systems, 24 (6), 6639-6649. doi: 10.1109/tits.2022.3147668 |
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2023 Journal Article Guest Editorial Introduction to the Special Issue on Deployment of Connected and Automated Vehicles in Mixed Traffic Environment and the Implications on Traffic Safety and EfficiencyFarah, Haneen, Olstam, Johan and Zheng, Zuduo (2023). Guest Editorial Introduction to the Special Issue on Deployment of Connected and Automated Vehicles in Mixed Traffic Environment and the Implications on Traffic Safety and Efficiency. IEEE Transactions on Intelligent Transportation Systems, 24 (6), 6432-6435. doi: 10.1109/tits.2023.3276596 |
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2023 Journal Article Fifth-order A-WENO path-conservative central-upwind scheme for behavioral non-equilibrium traffic modelsChu, Shaoshuai, Kurganov, Alexander, Mohammadian, Saeed and Zheng, Zuduo (2023). Fifth-order A-WENO path-conservative central-upwind scheme for behavioral non-equilibrium traffic models. Communications in Computational Physics, 33 (3), 692-732. doi: 10.4208/cicp.OA-2022-0263 |
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2023 Journal Article Stability evolution of car-following models considering asymmetric driving behaviorSun, Jie, Zheng, Zuduo and Sun, Jian (2023). Stability evolution of car-following models considering asymmetric driving behavior. Transportation Research Record: Journal of the Transportation Research Board, 2677 (8), 361-371. doi: 10.1177/03611981231156584 |
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2023 Journal Article Space sharing between pedestrians and micro-mobility vehicles: a systematic reviewZhang, Cheng, Du, Bo, Zheng, Zuduo and Shen, Jun (2023). Space sharing between pedestrians and micro-mobility vehicles: a systematic review. Transportation Research Part D: Transport and Environment, 116 103629, 1-18. doi: 10.1016/j.trd.2023.103629 |
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2023 Journal Article Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approachZhong, Miner, Kim, Jiwon and Zheng, Zuduo (2023). Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach. IEEE Open Journal of Intelligent Transportation Systems, 4, 14-29. doi: 10.1109/ojits.2022.3233904 |
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2023 Journal Article A learning-based discretionary lane-change decision-making model with driving style awarenessZhang, Yifan, Xu, Qian, Wang, Jianping, Wu, Kui, Zheng, Zuduo and Lu, Kejie (2023). A learning-based discretionary lane-change decision-making model with driving style awareness. IEEE Transactions on Intelligent Transportation Systems, 24 (1), 68-78. doi: 10.1109/tits.2022.3217673 |
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2022 Journal Article Corrigendum: “State of data platforms for connected vehicles and infrastructures” (Communications in Transportation Research (2021) 1, (100013), (S2772424721000135), (10.1016/j.commtr.2021.100013))Lim, Kai Li, Whitehead, Jake, Jia, Dongyao and Zheng, Zuduo (2022). Corrigendum: “State of data platforms for connected vehicles and infrastructures” (Communications in Transportation Research (2021) 1, (100013), (S2772424721000135), (10.1016/j.commtr.2021.100013)). Communications in Transportation Research, 2 100057, 100057. doi: 10.1016/j.commtr.2022.100057 |
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2022 Journal Article Predicting and explaining lane-changing behaviour using machine learning: a comparative studyAli, Yasir, Hussain, Fizza, Bliemer, Michiel C. J., Zheng, Zuduo and Haque, Md. Mazharul (2022). Predicting and explaining lane-changing behaviour using machine learning: a comparative study. Transportation Research Part C: Emerging Technologies, 145 103931, 1-20. doi: 10.1016/j.trc.2022.103931 |
