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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 |
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2022 Journal Article A generative car-following model conditioned on driving stylesZhang, Yifan, Chen, Xinhong, Wang, Jianping, Zheng, Zuduo and Wu, Kui (2022). A generative car-following model conditioned on driving styles. Transportation Research Part C: Emerging Technologies, 145 103926, 1-21. doi: 10.1016/j.trc.2022.103926 |
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2022 Journal Article A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environmentAli, Yasir, Haque, Md. Mazharul, Zheng, Zuduo and Afghari, Amir Pooyan (2022). A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment. Analytic Methods in Accident Research, 35 100221, 100221. doi: 10.1016/j.amar.2022.100221 |
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2022 Journal Article An extreme value theory approach to estimate crash risk during mandatory lane-changing in a connected environmentAli, Yasir, Haque, Md Mazharul and Zheng, Zuduo (2022). An extreme value theory approach to estimate crash risk during mandatory lane-changing in a connected environment. Analytic Methods in Accident Research, 33 100193, 100193. doi: 10.1016/j.amar.2021.100193 |
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2022 Journal Article Examining braking behaviour during failed lane-changing attempts in a simulated connected environment with driving aidsAli, Yasir, Bliemer, Michiel C.J., Haque, Md. Mazharul and Zheng, Zuduo (2022). Examining braking behaviour during failed lane-changing attempts in a simulated connected environment with driving aids. Transportation Research Part C: Emerging Technologies, 136 103531, 103531. doi: 10.1016/j.trc.2021.103531 |
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2022 Journal Article Processing, assessing, and enhancing the Waymo autonomous vehicle open dataset for driving behavior researchHu, Xiangwang, Zheng, Zuduo, Chen, Danjue, Zhang, Xi and Sun, Jian (2022). Processing, assessing, and enhancing the Waymo autonomous vehicle open dataset for driving behavior research. Transportation Research Part C: Emerging Technologies, 134 103490, 103490. doi: 10.1016/j.trc.2021.103490 |
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2021 Journal Article A car-following model for connected and automated vehicles with heterogeneous time delays under fixed and switching communication topologiesLi, Yongfu, Chen, Bangjie, Zhao, Hang, Peeta, Srinivas, Hu, Simon, Wang, Yibing and Zheng, Zuduo (2021). A car-following model for connected and automated vehicles with heterogeneous time delays under fixed and switching communication topologies. IEEE Transactions on Intelligent Transportation Systems, 23 (9), 1-13. doi: 10.1109/tits.2021.3134419 |
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2021 Journal Article Integrating safety into the fundamental relations of freeway traffic flows: a conflict-based safety assessment frameworkMohammadian, Saeed, Haque, Md. Mazharul, Zheng, Zuduo and Bhaskar, Ashish (2021). Integrating safety into the fundamental relations of freeway traffic flows: a conflict-based safety assessment framework. Analytic Methods in Accident Research, 32 100187, 100187. doi: 10.1016/j.amar.2021.100187 |
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2021 Journal Article State of data platforms for connected vehicles and infrastructuresLim, Kai Li, Whitehead, Jake, Jia, Dongyao and Zheng, Zuduo (2021). State of data platforms for connected vehicles and infrastructures. Communications in Transportation Research, 1 100013, 100013-1. doi: 10.1016/j.commtr.2021.100013 |
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2021 Journal Article Reasons, challenges, and some tools for doing reproducible transportation researchZheng, Zuduo (2021). Reasons, challenges, and some tools for doing reproducible transportation research. Communications in Transportation Research, 1 100004, 1-10. doi: 10.1016/j.commtr.2021.100004 |
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2021 Journal Article Modelling lane-changing execution behaviour in a connected environment: a grouped random parameters with heterogeneity-in-means approachAli, Yasir, Zheng, Zuduo and Haque, Md Mazharul (2021). Modelling lane-changing execution behaviour in a connected environment: a grouped random parameters with heterogeneity-in-means approach. Communications in Transportation Research, 1 100009, 1-14. doi: 10.1016/j.commtr.2021.100009 |
